Symptom Management and Supportive Care
Frailty Is an Independent Predictor of Survival in Older Patients With Colorectal Cancer NINA OMMUNDSEN,a,c,f TORGEIR B.WYLLER,a,c ARILD NESBAKKEN,a,d,i MARIT S. JORDHØY,a,e,h ARNE BAKKA,a,g EVA SKOVLUND,b SIRI ROSTOFTc a Institute of Clinical Medicine and bDepartment of Pharmaceutical Biosciences, School of Pharmacy, University of Oslo, Norway; Departments of cGeriatric Medicine and dGastrointestinal Surgery and eRegional Centre for Excellence in Palliative Care, South-East Norway, Oslo University Hospital, Oslo, Norway; Departments of fGeriatric and General Internal Medicine and gDigestive Surgery, Akershus University Hospital, Lørenskog, Norway; hCancer Unit, Innlandet Hospital Trust, Hamar, Norway; iK.G. Jebsen Colorectal Cancer Research Centre, Oslo, Norway
Disclosures of potential conflicts of interest may be found at the end of this article.
Key Words. Geriatric assessment x Colorectal neoplasms x Frail elderly x Mortality
Background. Colorectal cancer (CRC) is prevalent in the older population. Geriatric assessment (GA) has previously been found to predict treatment tolerance and postoperative complications in older cancer patients. The aim of this study was to explore whether GA also predicts 1-year and 5-year survival after CRC surgery in older patients and to compare the predictive power of GA with that of established prognostic factors such as TNM classification of malignant tumors (TNM) stage and age. Materials and Methods. A cohort of 178 CRC patients aged 70 and older were followed prospectively. All patients went through elective surgery, and GA was performed presurgery. The GA resulted in patients being divided into two groups: frail or nonfrail. All patients were followed for 5 years or until death. Data were analyzed by Kaplan-Meier plots and the Cox proportional hazards model.
Results. Seventy-six patients (43%) were frail, and one hundred and two (57%) were nonfrail. Twenty-three patients (13%) died during the first year after surgery. One-year survival was 80% in the frail group and 92% in the nonfrail group. Five-year survival was significantly lower in frail (24%) than nonfrail patients (66%), and this difference was apparent both within the stratums of TNM stages 0–II and TNM stage III. In multivariable analysis adjusting for TNM stage, age, and sex, frailty was an independent prognostic factor for survival. Conclusion. A GA-based frailty assessment predicts 1-year and 5-year survival in older patients after surgery for CRC. In localized and regional disease, the impact of frailty upon 5-year survival is comparable with that of TNM stage. The Oncologist 2014;19:1268–1275
Implications for Practice: Geriatric assessment has previously been found to predict several outcomes when treating older cancer patients, such as postoperative complications and treatment tolerance.The result of a geriatric assessment can be expressed as the patient’s degree of frailty. In this study, we find that frailty is a strong predictor for 5-year survival after surgery for colorectal cancer in a group of patients aged 75 and older. Performing a geriatric assessment took 20-60 minutes, and is recommended as part of the decision making process in older cancer patients.
INTRODUCTION Cancer is adiseaseofaging, withapproximately 60% ofallcancers and 70% of all cancer deaths occurring in people aged 65 and older [1]. Colorectal cancer (CRC) is no exception, with sharply increasing incidence rates with age in all industrialized countries [2]. In Norway, colorectal cancer is now the most frequent cancer in women aged 70 and older, and in men it is second only to prostate cancer [3]. CRC is also the second leading cause ofcancer death in Europe [3, 4]. Over the last decades, mortality rates from CRC have declined [4, 5], but this improvement in survival has been less evident in the older age groups [4, 6, 7]. Tumor stage at diagnosis is critical for prognosis and choice of treatment strategies [8]. In the older cancer patient,
prognosis and treatment decisions are also influenced by patient-related factors such as comorbidity and functional status. Therefore, the International Society for Geriatric Oncology (SIOG) recommends that a geriatric assessment (GA) should be performed in all cancer patients more than 70 years of age.The most frail patients seem to benefit most from a GA-based approach, and a two-step model including some form of screening may be used [9]. Geriatric assessment is widely used in clinical, nononcology geriatric practice, and its value for in-hospital patients in this setting has been demonstrated through randomized controlled trials [10]. It is a systematic assessment of the patient encompassing
CME
Correspondence: Nina Ommundsen, M.D., Geriatric Department, Building 37, Oslo University Hospital, P.O. Box 4956, Nydalen, 0424 Oslo, Norway. Telephone: 4740225685; E-Mail: [email protected] Received June 17, 2014; accepted for publication September 25, 2014; first published online in The Oncologist Express on October 29, 2014. ©AlphaMed Press 1083-7159/2014/$20.00/0 http://dx.doi.org/10.1634/ theoncologist.2014-0237
The Oncologist 2014;19:1268–1275 www.TheOncologist.com
©AlphaMed Press 2014
Downloaded from http://theoncologist.alphamedpress.org/ at McMaster University on December 22, 2014
ABSTRACT
Ommundsen, Wyller, Nesbakken et al.
1269
Table 1. Components of the geriatric assessment with cutoff values for frailty Component
Tool (scoring range)
Cutoff value for frailty
ADL
Barthel index (0–30 points) NEADL (0–66 points)a Number of systemic medications in daily use Cumulative Illness Rating Scale (grades 0–4) Mini Nutritional Assessment (0–30 points) Mini Mental State Examination (0–30 points) Geriatric Depression Scale (0–30 points)
,19 points
Use of medication Comorbidity Nutritional status Cognitive function Depression
.7 drugs Any grade 4 comorbidity or .2 grade 3 comorbidities ,17 points ,24 points .13 points
NEADL score of .43 points was only used for classifying a patient as fit [14]. Abbreviations: ADL, activities of daily living; NEADL, Nottingham Extended ADL Scale.
a
MATERIAL AND METHODS Study Group Patients were recruited from three university hospitals in the Oslo area: Oslo University Hospital, Ullevaal; Oslo University Hospital, Aker; and Akershus University Hospital.The inclusion period was from November 2006 to June 2008. All patients scheduled for elective surgery for confirmed or suspected colorectal cancer and aged 70 and older were eligible for inclusion. Patients had to be able to provide written consent. There were no other exclusion criteria.The study was approved by the Regional Committee for Medical and Health Research Ethics in South East Norway.
Validated scoring systems with predefined and established cutoff values for frailty were used for each domain (Table 1). We used a modified version of the criteria for frailty first proposed by Balducci and Extermann [12], described in detail previously [14]. If the patient scored outside the cutoff value within one or more of the domains, he was considered frail. For functional status, the Barthel index [18] and Nottingham Extended Activities for Daily Living Scale (NEADL) [19] were used. The Barthel index measures dependence in basic personal activities of daily living (ADL) such as showering, feeding, and walking. The index yields a score of 0–20 points, where 20 points signifies full independence. The NEADL measures dependence in the more complex daily activities, often referred to as instrumental ADL (IADL) [19]. Examples of such activities are domestic work, leisure activities, kitchen work, and mobility. The sum score ranges from 0 to 66 points, and a score above 43 points signifies independence in IADL. Data on comorbidity and number of systemic medications in daily use were gathered from the interview with the patient and from the patient records. Comorbidity was scored according to the revised Cumulative Illness Rating Scale (CIRS) [20, 21].This scale assesses 14 organ systems and rates comorbidities in each organ system according to degree of severity: from grade 0 (no comorbidity) to grade 4 (extremely severe comorbidity). Nutritional status was assessed with the 18-item Mini Nutritional Assessment [22], giving a score of 0–30 points, where ,17 points signifies malnourishment. For cognitive assessment, we used the Mini Mental State Examination [23], a widely used 20-item screening tool for cognitive impairment. The score ranges from 0 to 30 points, and a score below 24 is considered indicative of reduced cognitive abilities. Finally, for assessment of depression, we used the Geriatric Depression Scale, a 30-item yes/no questionnaire. A score of 14 or higher has been found to indicate depression with a sensitivity of 80% and specificity of 100% [24, 25]. The oncologists and surgeons responsible for the treatment were blinded to the results of the GA.
Downloaded from http://theoncologist.alphamedpress.org/ at McMaster University on December 22, 2014
a multitude of domains such as functional status, medication, comorbidities, nutrition, cognitive abilities, and signs of depression. The aim of the assessment in an older cancer patient is threefold: (a) to estimate the patient’s physiological reserves and capacity, (b) to serve as decision-making support, and (c) to detect other and potentially reversible conditions such as depression, malnourishment, and harmful polypharmacy [11]. The result of the GA may be expressed as an estimation of the patient’s frailty: is this a fit patient who will tolerate standard treatment or a frail patient who might profit from a more individualized approach [12]? In cancer patients, GA has been found to predict treatment tolerance [13] and postoperative complications [14], to identify previously unrecognized and potentially reversible conditions [15], and to predict mortality [16]. However, two recent reviews conclude that the evidence is still conflicting and that further research is needed to establish the role of GA in predicting outcomes and affecting treatment decisions [16, 17]. In a previous prospective study, we showed that frailty can predict short-term outcomes such as postoperative complications in a cohort of older colorectal cancer patients [14]. The aim of the current study was to explore whether a GA-based frailty assessment and individual components of GA were prognostic for 1-year and 5-year survival after surgery and to compare their prognostic impact to that of established prognostic factors such as tumor stage and chronological age.
All patients were examined in hospital 0–14 days before surgery by a medical doctor trained in geriatrics (S.R.). The doctor performed a geriatric assessment consisting of six domains: functional status, use of medication, comorbidities, nutritional status, cognitive abilities, and signs of depression.
www.TheOncologist.com
Outcome Variables and Explanatory Variables Follow-up was for 5 years or until death, when all-cause mortality data were gathered. Five-year survival after surgery was used as primary outcome variable. Survival data were collected from the National Registry of Norway. ©AlphaMed Press 2014
CME
Geriatric Assessment and Frailty Definition
Frailty Predicts Survival in Colorectal Cancer
1270
Table 2. Patient characteristics Entire sample (n 5 178) (%)
Nonfrail subgroup (n 5 102)
89 (50%) 79 (44%) 10 (6%)
30 41 5
59 38 5
102 (57%) 76 (43%)
43 33
59 43
174 (98%) 4 (2%)
72 4
102 0
52 (29%) 126 (71%)
23 53
29 73
8 (5%) 43 (24%) 57 (32%) 45 (25%) 21 (12%) 4 (2%)
5 19 22 18 10 2
3 24 35 27 11 2
118 (66%) 52 (29%) 8 (5%)
49 21 6
69 31 2
The table shows the demography, cancer type, tumor stage, and type of surgery for all 178 patients. Abbreviation: TNM, TNM classification of malignant tumors.
Asthemain explanatory variable, weused frailtystatus based on the GA. In a second multivariable analysis, the individual components of the GA were used as explanatory variables.
found to be significant in unadjusted analysis. Hazard ratios with a 95% confidence interval are reported for all variables.
RESULTS
CME
Statistical Analyses
Patient Characteristics
Analyses were performed using SPSS Statistics version 18. Time from surgery to death was estimated by Kaplan-Meier analysis and compared with log-rank tests. The Cox proportional hazards regression model was applied to estimate independent effects of the different explanatory variables. The assumption of proportional hazards was checked by visual inspection of log minus log plots. To detect potential multicollinearity, we estimated pairwise correlation between explanatory variables and compared standard errors of the estimates from unadjusted and adjusted models. In addition, variance inflation factors were informally inspected. All variables that were statistically significant in unadjusted analyses with a p value , 0.05 were entered into the multivariable model. Subsequently variables were selected by backward elimination to reduce the model to include statistically significant variables only. Two Cox models for 5year survival were made.The first model included frailty as the main explanatory variable, correcting for tumor stage, age, and sex.The second model included the individual frailty indicators as explanatory variables, correcting for tumor stage and sex. Age was not included in the second model, because it was not
One hundred ninety-five patients were assessed for eligibility. Ten were not able to give consent, refused participation, or were deemed unfit for surgery and thus excluded from the study presurgery. Seven patients were excluded postsurgery because complete GA data had not been collected, surgical resection had not been performed, or reoperation had been performed for other reasons. Details on inclusion into the study have been published previously [14]. The final study cohort consisted of 178 patients. As seen in Table 2, the median age was 80 years (range, 70–94 years), and 57% were women. Almost all patients were living at home before surgery, and the majority (83%) were independent in IADL. However, comorbidities were common, with 74% of patients having moderate or serious comorbidity according to CIRS. Cognitive impairment was found in 7%, and malnutrition was found in 10%. Based on the GA data and the predefined cutoff values for each domain of the geriatric assessment, 76 patients (43%) were frail, and 102 (57%) were nonfrail. Fifty-two patients (29%) had rectal cancer. Eight patients had carcinoma in situ and were classified as TNM stage 0. A large majority had
OTncologist he
©AlphaMed Press 2014
®
Downloaded from http://theoncologist.alphamedpress.org/ at McMaster University on December 22, 2014
Age at time of surgery 70–79 years 80–89 years 901 years Sex Female Male Housing Private home Institution Tumor location Rectum Colon TNM stage 0 I II III IV Unclassified Surgery Open Laparoscopic Converted
Frail subgroup (n5 76)
Ommundsen, Wyller, Nesbakken et al.
1271
Association Between Frailty and Survival In frail and nonfrail patients, 1-year survival was 80% and 92%, respectively.The difference in survival increased further during the study period. In frail patients, 5-year survival was 24%, and median survival was 24 months. In nonfrail patients, 5-year survival was 66% (log rank p , .001) (Fig. 1). In univariate analysis, frailty, tumor stage, and sex were all prognostic factors for 5-year survival (Table 3). Age above 80 yearsas compared with age of 70–79 years was nota prognostic factor in the univariate analysis (Table 3) and was therefore not a part of the multivariable model. In multivariable Cox regression analysis, frailty status was a significant prognostic factor for survival when adjusting for TNM stage and sex, with a hazard ratio (HR) of 3.6 (95% confidence interval [CI] 2.3–5.5). Within the strata of localized and regional disease, 5-year survival was significantly higher in nonfrail than in frail patients (Fig. 2), with log-rank p value of ,0.001 in localized disease and of p 5 .007 in regional disease. In metastatic disease, mortality was high in both frail and nonfrail patients (log-rank p 5 .2).
Association Between Individual Frailty Indicators and 5-Year Survival We further analyzed the impact of the single components of the GA upon survival. In univariate analysis, comorbidity,
www.TheOncologist.com
nutritional status, cognitive function, polypharmacy, and IADL dependency were all prognostic factors for survival. Severe comorbidity and IADL dependency had the strongest associations with decreased survival, with a HR of 2.8 (1.8–4.3) and 2.8 (1.8–4.4), respectively.The only individual GA element that was not a significant prognostic factor for 5-year survival was depression (Table 4). In multivariable analysis correcting for TNM stage and sex, IADL function, comorbidity, and nutritional status remained individual prognostic factors for 5-year survival (Table 4). Because age had already been found to be without statistical significance in univariate analysis, we did not correct for age in this multivariable analysis.
DISCUSSION Our main finding was that frailty predicts both short-term (1year) and long-term (5-year) survival after elective surgery for colorectal cancer in older patients. The individual components of GA that were independently prognostic for survival were functional status (IADL), comorbidity, and nutritional status. As expected, TNM stage had a strong prognostic impact on survival, but the association between frailty and mortality remained pronounced within TNM stages 0–II, as well as within stage III. Of note, in tumor stages 0–II, only 28% of frail patients were alive after 5 years compared with 77% of nonfrail patients. In multivariable analysis, being frail (as opposed to nonfrail) implied a higher HR for mortality than having TNM stage III as opposed to stages 0–II. Thus, whereas tumor stage is essential for the prognosis and treatment of older patients with colorectal cancer, assessing frailty seems to be comparable in importance for evaluating overall prognosis in localized and regional disease. ©AlphaMed Press 2014
CME
potentially curable disease with 61% with TNM stages 0–II (localized disease), 25% with TNM stage III (regional disease), and only 12% with metastatic disease (TNM stage IV). During the first year after surgery, 23 patients (13%) died, and 93 (52%) died within 5 years after surgery. Median followup was 57.5 months (range, 1–60). There was no association between frailty and tumor stage: 43% of patients with localized disease, 40% of patients with regional disease and 48% of patients with distant metastases were frail.
Downloaded from http://theoncologist.alphamedpress.org/ at McMaster University on December 22, 2014
Figure 1. Five-year overall survival by frailty status. Kaplan-Meier plot of 5-year survival in frail (n 5 76) versus nonfrail (n 5 102) patients.
Frailty Predicts Survival in Colorectal Cancer
1272
Table 3. Predictive models for survival (Cox proportional hazards) with frailty and tumor stage Unadjusted models HR (95% CI)
p
HR (95% CI)
1a 1.2 (0.8–1.7)
.48
1a 1.6 (1.1–2.5)
.02
1a 1.5 (1.0–2.3)
p
.04
1a ,.001 1a ,.001 1.6 (1.0–2.6) 1.7 (1.0–2.7) 7.1 (4.1–12.3) 7.3 (4.1–13.0) 1a 3.3 (2.2–5.1)
,.001 1a 3.6 (2.3–5.5)
Downloaded from http://theoncologist.alphamedpress.org/ at McMaster University on December 22, 2014
Age 70–79 years .80 years Sex Female Male TNM stage 0–II III IV Frailty statusb Nonfrail Frail
Adjusted model
,.001
The table shows Cox proportional hazards model with univariate and multivariable analysis of frailty and tumor stage as predictors for 5-year survival. a Reference group. b For definition see text and Table 1. Abbreviations: CI, confidence interval; HR, hazard ratio; TNM, TNM classification of malignant tumors.
CME
Two recent reviews [16, 17] have summarized the prognostic properties of GA in older cancer patients. Puts et al. [17] found 13 prospective studies addressing the association between GA domains and mortality in different cancer groups. Although their conclusion is that the evidence so far is insufficient, most of the identified studies reported mental health, comorbidity, polypharmacy, malnutrition, and ADL impairments to be indicators of importance. Hamaker et al. [16] reviewed 25 studies and found comorbidity and malnutrition to be the most consistently reported risk factors for mortality. Our findings accord well with these reviews, but whereas they assessedtheimpactofGAdomains in a varietyofcancerpatients and thus found that the primary reports diverged in their conclusions, we provide data on the prognostic validity of GA in a well-defined homogeneous group of CRC patients. In a recent large study restricted to CRC patients, Gooiker et al. [26] likewise found comorbidity to be a profound risk factor for mortality during the first postoperative year, in addition to age, tumor stage, emergency surgery, and postoperative adverse events. Other GA components such as functional status were, however, not included in that study. Major strengths of our study are a prospective design with a long follow-up period, a standardized GA performed in the same preoperative setting of a truly aged population, and the fact that the same doctor performed all GAs. However, there are also weaknesses limiting the external validity of the results. The number of participants was limited, and they represent a selected group of patients who were referred to and accepted for elective surgery. Furthermore, the frailty assessment in these analyses did not include any physical performance measures such as gait speed. Recent studies have shown that clinical frailty scores that contain one or two physical performance measures have better predictive ability
Figure 2. Five-year survival in different tumor stages by frailty status. Kaplan-Meier plots of 5-year survival in frail versus nonfrail patients are stratified according to TNM classification of malignant tumors (TNM) stage. (A): TNM stages 0–II (localized disease; n 5 108; log rank p , .001). (B): TNM stage III (regional disease; n 5 45; log rank p 5 .007). (C): TNM stage IV (distant mestastases; n 5 21; log rank p 5 .2).
than those without [27]. In addition, cause of death is not reported. Further studies are warranted to explore whether frailty is of prognostic value for cancer-specific mortality in this population.
OTncologist he
©AlphaMed Press 2014
®
Ommundsen, Wyller, Nesbakken et al.
1273
Table 4. Predictive models for survival (Cox proportional hazards) with the individual frailty indicators
HR (95% CI)
p
HR (95% CI)
p
,.001
1a 1.6 (1.1–2.5)
.02
1a 1.6 (1.0–2.6) 7.1 (4.1–12.3)
,.001
1a 1.5 (0.9–2.5) 8.8 (4.9–15.7)
1a 2.8 (1.8–4.4)
,.001
1a 2.3 (1.3–4.0)
.006
1a 2.8 (1.8–4.3)
,.001
1a 1.9 (1.1–3.2)
.02
1a 2.2 (1.1–4.3)
.03
1a 2.3 (1.4–4.1)
.003
1a 1.8 (1.0–3.3)
.04
1a 2.2 (1.1–4.2)
.02
1a 1.4 (0.7–2.6)
.33
The table shows the Cox proportional hazards model with univariate and multivariable analysis of the individual frailty indicators and tumor stage as predictors for 5-year survival. An adjusted model was used with the following variables: sex, TNM stage, IADL function, comorbidity, number of systemic drugs, nutritional status, and cognitive function. a Reference group. b For definition, see Table 1. Abbreviations: CI, confidence interval; CIRS, Cumulative Illness Rating Scale; GDS, Geriatric Depression Scale; HR, hazard ratio; IADL, Instrumental activities of daily living; MMSE, Mini Mental State Evaluation; MNA, Mini Nutritional Assessment; NEADL, Nottingham Extended Activities of Daily Living Scale; TNM, TNM classification of malignant tumors.
Undertreatment and overtreatment are well-known pitfalls in geriatric oncology. Many of the patients are frail with limited remaining life expectancy. Understanding the heterogeneity of the aging process, in which some patients become frail while others remain fit and independent despite advanced chronological age, is of critical importance in prognostics and decision making.To avoid overtreatment, an essential question is whether the patient is going to live long enough to experience complications from his cancer disease [28]. In order to be able to answer this question, the treating physician needs knowledge of both the life expectancy of the patient and the expected progression of the cancer if left untreated.These are difficult tasks, and elements of uncertainty are almost always present. In our cohort, 93% of frail patients survived the first 3 months after surgery, and 80% of frail patients survived the first year. This may imply that overtreatment was not a major concern in our population. However, many older patients consider preserved physical and cognitive function after treatment to be more important than prolonged survival
www.TheOncologist.com
per se [29]. We have previously looked at physical function in a subsample of 84 patients from the same cohort. In that study, we found a significant reduction in ADL and IADL scores from the preoperative state until 16–28 months after surgery [30]. Approximately one-third of the patients had lost ADL function, while two-thirds had lost IADL function. Undertreatment of older cancer patients has been reported in several studies [31, 32], although there may have been some improvement in this field in recent years [33]. Undertreatment of colorectal cancer may give rise to serious and painful complications such as bleeding, bowel obstruction, and perforation. Emergency surgery carries a far higher risk than elective surgery [26], especially in older patients. Elective surgery is the preferred treatment, either for cure or for palliation, and after careful selection of patients [34, 35]. Despite recommendations, GA is still not fully incorporated into everyday clinical practice. One reason may be feasibility and time needed for the assessment. In our study, the assessment ©AlphaMed Press 2014
Downloaded from http://theoncologist.alphamedpress.org/ at McMaster University on December 22, 2014
Sex Female Male TNM stage 0–II III IV IADL function Independent (NEADL .43) Dependent (NEADL ,44) Comorbidity (CIRS) No/mild Severeb Systemic drugs ,8 .7 Nutritional status Normal (MNA .16) Malnourished (MNA ,17) Cognitive function Normal (MMSE .23) Reduced (MMSE ,24) Depression Not depressed (GDS ,14) Depressed (GDS .13)
Adjusted model
CME
Unadjusted models
Frailty Predicts Survival in Colorectal Cancer
1274
CONCLUSION Our study provides evidence on the prognostic value of GAbased frailty in older cancer patients. Geriatric assessment adds information about patient’s short-term and long-term overall survival, which, along with information of tumor stage at diagnosis, is of critical importance for decision making in older cancer patients. Performing a GA in older cancer patients
is recommended by the SIOG but is not yet fully incorporated into everyday clinical practice. For future research, emphasis should be on patient-centered outcomes such as cognitive and physical function and self-reported health. In addition, because evidence from randomized controlled trials on the effects of GA is lacking, intervention studies are needed.
ACKNOWLEDGMENT Funding for this study was provided through a grant from the Norwegian Cancer Society.
AUTHOR CONTRIBUTIONS Conception/Design: Nina Ommundsen, Torgeir B. Wyller, Arild Nesbakken, Marit S. Jordhøy, Arne Bakka, Eva Skovlund, Siri Rostoft Provision of study material or patients: Arild Nesbakken, Arne Bakka Collection and/or assembly of data: Nina Ommundsen, Siri Rostoft Data analysis and interpretation: Nina Ommundsen, Torgeir B. Wyller, Arild Nesbakken, Marit S. Jordhøy, Eva Skovlund, Siri Rostoft Manuscript writing: Nina Ommundsen, Torgeir B. Wyller, Arild Nesbakken, Marit S. Jordhøy, Arne Bakka, Eva Skovlund, Siri Rostoft Final approval of manuscript: Nina Ommundsen, Torgeir B. Wyller, Arild Nesbakken, Marit S. Jordhøy, Arne Bakka, Eva Skovlund, Siri Rostoft
DISCLOSURES The authors indicated no financial relationships.
REFERENCES 1. Hurria A, Gupta S, Zauderer M et al. Developing a cancer-specific geriatric assessment: A feasibility study. Cancer 2005;104:1998–2005.
11. Alibhai SMH. Comprehensive geriatric assessment in older patients with cancer: Two steps forward? J Geriatr Oncol 2013;4:205–207.
2. Parkin DM, Bray F, Ferlay J et al. Global cancer statistics, 2002. CA Cancer J Clin 2005;55:74–108.
12. Balducci L, Extermann M. Management of cancer in the older person: A practical approach.The Oncologist 2000;5:224–237.
3. Cancer Registry of Norway. Cancer in Norway 2010: Cancer Incidence, Mortality, Survival and Prevalence in Norway. Oslo, Norway: Cancer Registry of Norway, 2012. 4. Brenner H, Bouvier AM, Foschi R et al. Progress in colorectal cancer survival in Europe from the late 1980s to the early 21st century: The EUROCARE study. Int J Cancer 2012;131: 1649–1658. 5. Angell-Andersen E, Tretli S, Coleman MP et al. Colorectal cancer survival trends in Norway 1958–1997. Eur J Cancer 2004;40:734–742. 6. Morris EJA, Sandin F, Lambert PC et al. A population-based comparison of the survival of patients with colorectal cancer in England, Norway and Sweden between 1996 and 2004. Gut 2011;60: 1087–1093. 7. Nedrebø BS, Søreide K, Eriksen MT et al. Survival effect of implementing national treatment strategies for curatively resected colonic and rectal cancer. Br J Surg 2011;98:716–723. 8. Hari DM, Leung AM, Lee J-H et al. AJCC cancer staging manual 7th edition criteria for colon cancer: Do the complex modifications improve prognostic assessment? J Am Coll Surg 2013;217: 181–190.
CME
9. Wildiers H, Heeren P, Puts M et al. International society of geriatric oncology consensus on geriatric assessment in older patients with cancer. J Clin Oncol 2014;32:2595–2603. 10. Ellis G, Whitehead MA, O’Neill D et al. Comprehensive geriatric assessment for older adults admitted to hospital. Cochrane Database Syst Rev 2011;CD006211.
13. Clough-Gorr KM, Stuck AE,Thwin SS et al. Older breast cancer survivors: Geriatric assessment domains are associated with poor tolerance of treatment adverse effects and predict mortality over 7 years of follow-up. J Clin Oncol 2010;28: 380–386. 14. Kristjansson SR, Nesbakken A, Jordhøy MS et al. Comprehensive geriatric assessment can predict complications in elderly patients after elective surgery for colorectal cancer: A prospective observational cohort study. Crit Rev Oncol Hematol 2010;76:208–217. 15. Extermann M, Meyer J, McGinnis M et al. A comprehensive geriatric intervention detects multiple problems in older breast cancer patients. Crit Rev Oncol Hematol 2004;49:69–75. 16. Hamaker ME,Vos AG, Smorenburg CH et al.The value of geriatric assessments in predicting treatment tolerance and all-cause mortality in older patients with cancer. The Oncologist 2012;17: 1439–1449.
Illness Rating Scale. Psychiatry Res 1992;41:237– 248. 21. Salvi F, Miller MD, Grilli A et al. A manual of guidelines to score the modified cumulative illness rating scale and its validation in acute hospitalized elderly patients. J Am Geriatr Soc 2008;56:1926– 1931. 22. Guigoz Y. The mini nutritional assessment (MNA) review of the literature–what does it tell us? J Nutr Health Aging 2006;10:466–485. 23. Folstein MF, Folstein SE, McHugh PR. “Minimental state”: A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12:189–198. 24. Yesavage JA, Brink TL, Rose TL et al. Development and validation of a geriatric depression screening scale: A preliminary report. J Psychiatr Res 1982–1983;17:37–49. 25. Brink TL, Yesavage JA, Lum O et al. Screening tests for geriatric depression. Clin Gerontol 1982;1: 37–43. 26. Gooiker GA, Dekker JW, Bastiaannet E et al. Risk factors for excess mortality in the first year after curative surgery for colorectal cancer. Ann Surg Oncol 2012;19:2428–2434.
17. Puts MTE, Hardt J, Monette J et al. Use of geriatric assessment for older adults in the oncology setting: A systematic review. J Natl Cancer Inst 2012; 104:1133–1163.
27. Woo J, Leung J, Morley JE. Comparison of frailty indicators based on clinical phenotype and the multiple deficit approach in predicting mortality and physical limitation. J Am Geriatr Soc 2012;60: 1478–1486.
18. Mahoney FI, Barthel DW. Functional evaluation: The Barthel index. Md State Med J 1965;14: 61–65.
28. Balducci L, Colloca G, Cesari M et al. Assessment and treatment of elderly patients with cancer. Surg Oncol 2010;19:117–123.
19. Lincoln NB, Gladman JRF. The Extended Activities of Daily Living Scale: A further validation. Disabil Rehabil 1992;14:41–43.
29. Fried TR, Bradley EH, Towle VR et al. Understanding the treatment preferences of seriously ill patients. N Engl J Med 2002;346: 1061–1066.
20. Miller MD, Paradis CF, Houck PR et al. Rating chronic medical illness burden in geropsychiatric practice and research: Application of the Cumulative
30. Rønning B, Wyller TB, Jordhøy MS et al. Frailty indicators and functional status in older patients
OTncologist he
©AlphaMed Press 2014
®
Downloaded from http://theoncologist.alphamedpress.org/ at McMaster University on December 22, 2014
took 20–60 minutes per patient. To reduce the time needed for the assessment, one might wish to exclude some of its domains and assess only those with the strongest predictive power. In our study, these were comorbidity, functional status, and nutritional status. However, the evidence regarding the predictive value of individual domains of the GA is still inconsistent [16]. In addition, some domains have obvious clinical value irrespective of predictive power. For example, it is essential to discover cognitive dysfunction in a patient prior to discussing consent and when providing treatment that requires the patient to be alert of possible complications. Depression in older cancer patients is prevalent, causes considerable morbidity and suffering, and can be treated [36]. Polypharmacy is a large and increasing problem in the older population, causing considerable morbidity and mortality [37].Therefore, a full GA is still recommended.
Ommundsen, Wyller, Nesbakken et al.
1275
after colorectal cancer surgery. J Geriatr Oncol 2014; 5:26–32.
cancer in South Netherlands, 1995 to 2002. Cancer 2006;106:2734–2742.
31. Van Leeuwen BL, Rosenkranz KM, Feng LL et al. The effect of under-treatment of breast cancer in women 80 years of age and older. Crit Rev Oncol Hematol 2011;79:315–320.
33. Bernardi D, Errante D,Tirelli U et al. Insight into the treatment of cancer in older patients: Developments in the last decade. Cancer Treat Rev 2006;32: 277–288. 34. Simmonds PD, Best L, George S et al. Surgery for colorectal cancer in elderly patients: A systematic review. Lancet 2000;356:968– 974.
32. Vulto AJ, Lemmens VE, Louwman MW et al.The influence of age and comorbidity on receiving radiotherapy as part of primary treatment for
CME
35. Kunitake H, Zingmond DS, Ryoo J et al. Caring for octogenarian and nonagenarian patients with colorectal cancer: What should our standards and expectations be? Dis Colon Rectum 2010;53:735–743. 36. Mottram P, Wilson K, Strobl J. Antidepressants for depressed elderly. Cochrane Database Syst Rev 2006;CD003491. 37. Hajjar ER, Cafiero AC, Hanlon JT. Polypharmacy in elderly patients. Am J Geriatr Pharmacother 2007; 5:345–351.
This article is available for continuing medical education credit at CME.TheOncologist.com.
CME
Implications for Practice: This article explains how to conduct a geriatric assessment, how to implement it into clinical practice, and how to use the results of the assessment in clinical oncology practice. Furthermore, information is provided about available resources on geriatric assessment as well as geriatric assessment and screening tools, and important challenges of implementing geriatric assessment in practice are highlighted.
Downloaded from http://theoncologist.alphamedpress.org/ at McMaster University on December 22, 2014
For Further Reading: Schroder Sattar, Shabbir M.H. Alibhai, Hans Wildiers et al. How to Implement a Geriatric Assessment in Your Clinical Practice. The Oncologist 2014;19:1056–1068.
www.TheOncologist.com
©AlphaMed Press 2014
References
This article cites 34 articles, 5 of which you can access for free at: http://theoncologist.alphamedpress.org/content/19/12/1268.full.html#ref-list-1
Downloaded from http://theoncologist.alphamedpress.org/ at McMaster University on December 22, 2014
Frailty Is an Independent Predictor of Survival in Older Patients With Colorectal Cancer Nina Ommundsen, Torgeir B. Wyller, Arild Nesbakken, Marit S. Jordhøy, Arne Bakka, Eva Skovlund and Siri Rostoft The Oncologist 2014, 19:1268-1275. doi: 10.1634/theoncologist.2014-0237 originally published online October 29, 2014
Downloaded from http://theoncologist.alphamedpress.org/ at McMaster University on December 22, 2014
The online version of this article, along with updated information and services, is located on the World Wide Web at: http://theoncologist.alphamedpress.org/content/19/12/1268
Frailty Is an Independent Predictor of Survival in Older Patients With Colorectal Cancer NINA OMMUNDSEN,a,c,f TORGEIR B.WYLLER,a,c ARILD NESBAKKEN,a,d,i MARIT S. JORDHØY,a,e,h ARNE BAKKA,a,g EVA SKOVLUND,b SIRI ROSTOFTc a Institute of Clinical Medicine and bDepartment of Pharmaceutical Biosciences, School of Pharmacy, University of Oslo, Norway; Departments of cGeriatric Medicine and dGastrointestinal Surgery and eRegional Centre for Excellence in Palliative Care, South-East Norway, Oslo University Hospital, Oslo, Norway; Departments of fGeriatric and General Internal Medicine and gDigestive Surgery, Akershus University Hospital, Lørenskog, Norway; hCancer Unit, Innlandet Hospital Trust, Hamar, Norway; iK.G. Jebsen Colorectal Cancer Research Centre, Oslo, Norway
Disclosures of potential conflicts of interest may be found at the end of this article.
Key Words. Geriatric assessment x Colorectal neoplasms x Frail elderly x Mortality
Background. Colorectal cancer (CRC) is prevalent in the older population. Geriatric assessment (GA) has previously been found to predict treatment tolerance and postoperative complications in older cancer patients. The aim of this study was to explore whether GA also predicts 1-year and 5-year survival after CRC surgery in older patients and to compare the predictive power of GA with that of established prognostic factors such as TNM classification of malignant tumors (TNM) stage and age. Materials and Methods. A cohort of 178 CRC patients aged 70 and older were followed prospectively. All patients went through elective surgery, and GA was performed presurgery. The GA resulted in patients being divided into two groups: frail or nonfrail. All patients were followed for 5 years or until death. Data were analyzed by Kaplan-Meier plots and the Cox proportional hazards model.
Results. Seventy-six patients (43%) were frail, and one hundred and two (57%) were nonfrail. Twenty-three patients (13%) died during the first year after surgery. One-year survival was 80% in the frail group and 92% in the nonfrail group. Five-year survival was significantly lower in frail (24%) than nonfrail patients (66%), and this difference was apparent both within the stratums of TNM stages 0–II and TNM stage III. In multivariable analysis adjusting for TNM stage, age, and sex, frailty was an independent prognostic factor for survival. Conclusion. A GA-based frailty assessment predicts 1-year and 5-year survival in older patients after surgery for CRC. In localized and regional disease, the impact of frailty upon 5-year survival is comparable with that of TNM stage. The Oncologist 2014;19:1268–1275
Implications for Practice: Geriatric assessment has previously been found to predict several outcomes when treating older cancer patients, such as postoperative complications and treatment tolerance.The result of a geriatric assessment can be expressed as the patient’s degree of frailty. In this study, we find that frailty is a strong predictor for 5-year survival after surgery for colorectal cancer in a group of patients aged 75 and older. Performing a geriatric assessment took 20-60 minutes, and is recommended as part of the decision making process in older cancer patients.
INTRODUCTION Cancer is adiseaseofaging, withapproximately 60% ofallcancers and 70% of all cancer deaths occurring in people aged 65 and older [1]. Colorectal cancer (CRC) is no exception, with sharply increasing incidence rates with age in all industrialized countries [2]. In Norway, colorectal cancer is now the most frequent cancer in women aged 70 and older, and in men it is second only to prostate cancer [3]. CRC is also the second leading cause ofcancer death in Europe [3, 4]. Over the last decades, mortality rates from CRC have declined [4, 5], but this improvement in survival has been less evident in the older age groups [4, 6, 7]. Tumor stage at diagnosis is critical for prognosis and choice of treatment strategies [8]. In the older cancer patient,
prognosis and treatment decisions are also influenced by patient-related factors such as comorbidity and functional status. Therefore, the International Society for Geriatric Oncology (SIOG) recommends that a geriatric assessment (GA) should be performed in all cancer patients more than 70 years of age.The most frail patients seem to benefit most from a GA-based approach, and a two-step model including some form of screening may be used [9]. Geriatric assessment is widely used in clinical, nononcology geriatric practice, and its value for in-hospital patients in this setting has been demonstrated through randomized controlled trials [10]. It is a systematic assessment of the patient encompassing
CME
Correspondence: Nina Ommundsen, M.D., Geriatric Department, Building 37, Oslo University Hospital, P.O. Box 4956, Nydalen, 0424 Oslo, Norway. Telephone: 4740225685; E-Mail: [email protected] Received June 17, 2014; accepted for publication September 25, 2014; first published online in The Oncologist Express on October 29, 2014. ©AlphaMed Press 1083-7159/2014/$20.00/0 http://dx.doi.org/10.1634/ theoncologist.2014-0237
The Oncologist 2014;19:1268–1275 www.TheOncologist.com
©AlphaMed Press 2014
Downloaded from http://theoncologist.alphamedpress.org/ at McMaster University on December 22, 2014
ABSTRACT
Ommundsen, Wyller, Nesbakken et al.
1269
Table 1. Components of the geriatric assessment with cutoff values for frailty Component
Tool (scoring range)
Cutoff value for frailty
ADL
Barthel index (0–30 points) NEADL (0–66 points)a Number of systemic medications in daily use Cumulative Illness Rating Scale (grades 0–4) Mini Nutritional Assessment (0–30 points) Mini Mental State Examination (0–30 points) Geriatric Depression Scale (0–30 points)
,19 points
Use of medication Comorbidity Nutritional status Cognitive function Depression
.7 drugs Any grade 4 comorbidity or .2 grade 3 comorbidities ,17 points ,24 points .13 points
NEADL score of .43 points was only used for classifying a patient as fit [14]. Abbreviations: ADL, activities of daily living; NEADL, Nottingham Extended ADL Scale.
a
MATERIAL AND METHODS Study Group Patients were recruited from three university hospitals in the Oslo area: Oslo University Hospital, Ullevaal; Oslo University Hospital, Aker; and Akershus University Hospital.The inclusion period was from November 2006 to June 2008. All patients scheduled for elective surgery for confirmed or suspected colorectal cancer and aged 70 and older were eligible for inclusion. Patients had to be able to provide written consent. There were no other exclusion criteria.The study was approved by the Regional Committee for Medical and Health Research Ethics in South East Norway.
Validated scoring systems with predefined and established cutoff values for frailty were used for each domain (Table 1). We used a modified version of the criteria for frailty first proposed by Balducci and Extermann [12], described in detail previously [14]. If the patient scored outside the cutoff value within one or more of the domains, he was considered frail. For functional status, the Barthel index [18] and Nottingham Extended Activities for Daily Living Scale (NEADL) [19] were used. The Barthel index measures dependence in basic personal activities of daily living (ADL) such as showering, feeding, and walking. The index yields a score of 0–20 points, where 20 points signifies full independence. The NEADL measures dependence in the more complex daily activities, often referred to as instrumental ADL (IADL) [19]. Examples of such activities are domestic work, leisure activities, kitchen work, and mobility. The sum score ranges from 0 to 66 points, and a score above 43 points signifies independence in IADL. Data on comorbidity and number of systemic medications in daily use were gathered from the interview with the patient and from the patient records. Comorbidity was scored according to the revised Cumulative Illness Rating Scale (CIRS) [20, 21].This scale assesses 14 organ systems and rates comorbidities in each organ system according to degree of severity: from grade 0 (no comorbidity) to grade 4 (extremely severe comorbidity). Nutritional status was assessed with the 18-item Mini Nutritional Assessment [22], giving a score of 0–30 points, where ,17 points signifies malnourishment. For cognitive assessment, we used the Mini Mental State Examination [23], a widely used 20-item screening tool for cognitive impairment. The score ranges from 0 to 30 points, and a score below 24 is considered indicative of reduced cognitive abilities. Finally, for assessment of depression, we used the Geriatric Depression Scale, a 30-item yes/no questionnaire. A score of 14 or higher has been found to indicate depression with a sensitivity of 80% and specificity of 100% [24, 25]. The oncologists and surgeons responsible for the treatment were blinded to the results of the GA.
Downloaded from http://theoncologist.alphamedpress.org/ at McMaster University on December 22, 2014
a multitude of domains such as functional status, medication, comorbidities, nutrition, cognitive abilities, and signs of depression. The aim of the assessment in an older cancer patient is threefold: (a) to estimate the patient’s physiological reserves and capacity, (b) to serve as decision-making support, and (c) to detect other and potentially reversible conditions such as depression, malnourishment, and harmful polypharmacy [11]. The result of the GA may be expressed as an estimation of the patient’s frailty: is this a fit patient who will tolerate standard treatment or a frail patient who might profit from a more individualized approach [12]? In cancer patients, GA has been found to predict treatment tolerance [13] and postoperative complications [14], to identify previously unrecognized and potentially reversible conditions [15], and to predict mortality [16]. However, two recent reviews conclude that the evidence is still conflicting and that further research is needed to establish the role of GA in predicting outcomes and affecting treatment decisions [16, 17]. In a previous prospective study, we showed that frailty can predict short-term outcomes such as postoperative complications in a cohort of older colorectal cancer patients [14]. The aim of the current study was to explore whether a GA-based frailty assessment and individual components of GA were prognostic for 1-year and 5-year survival after surgery and to compare their prognostic impact to that of established prognostic factors such as tumor stage and chronological age.
All patients were examined in hospital 0–14 days before surgery by a medical doctor trained in geriatrics (S.R.). The doctor performed a geriatric assessment consisting of six domains: functional status, use of medication, comorbidities, nutritional status, cognitive abilities, and signs of depression.
www.TheOncologist.com
Outcome Variables and Explanatory Variables Follow-up was for 5 years or until death, when all-cause mortality data were gathered. Five-year survival after surgery was used as primary outcome variable. Survival data were collected from the National Registry of Norway. ©AlphaMed Press 2014
CME
Geriatric Assessment and Frailty Definition
Frailty Predicts Survival in Colorectal Cancer
1270
Table 2. Patient characteristics Entire sample (n 5 178) (%)
Nonfrail subgroup (n 5 102)
89 (50%) 79 (44%) 10 (6%)
30 41 5
59 38 5
102 (57%) 76 (43%)
43 33
59 43
174 (98%) 4 (2%)
72 4
102 0
52 (29%) 126 (71%)
23 53
29 73
8 (5%) 43 (24%) 57 (32%) 45 (25%) 21 (12%) 4 (2%)
5 19 22 18 10 2
3 24 35 27 11 2
118 (66%) 52 (29%) 8 (5%)
49 21 6
69 31 2
The table shows the demography, cancer type, tumor stage, and type of surgery for all 178 patients. Abbreviation: TNM, TNM classification of malignant tumors.
Asthemain explanatory variable, weused frailtystatus based on the GA. In a second multivariable analysis, the individual components of the GA were used as explanatory variables.
found to be significant in unadjusted analysis. Hazard ratios with a 95% confidence interval are reported for all variables.
RESULTS
CME
Statistical Analyses
Patient Characteristics
Analyses were performed using SPSS Statistics version 18. Time from surgery to death was estimated by Kaplan-Meier analysis and compared with log-rank tests. The Cox proportional hazards regression model was applied to estimate independent effects of the different explanatory variables. The assumption of proportional hazards was checked by visual inspection of log minus log plots. To detect potential multicollinearity, we estimated pairwise correlation between explanatory variables and compared standard errors of the estimates from unadjusted and adjusted models. In addition, variance inflation factors were informally inspected. All variables that were statistically significant in unadjusted analyses with a p value , 0.05 were entered into the multivariable model. Subsequently variables were selected by backward elimination to reduce the model to include statistically significant variables only. Two Cox models for 5year survival were made.The first model included frailty as the main explanatory variable, correcting for tumor stage, age, and sex.The second model included the individual frailty indicators as explanatory variables, correcting for tumor stage and sex. Age was not included in the second model, because it was not
One hundred ninety-five patients were assessed for eligibility. Ten were not able to give consent, refused participation, or were deemed unfit for surgery and thus excluded from the study presurgery. Seven patients were excluded postsurgery because complete GA data had not been collected, surgical resection had not been performed, or reoperation had been performed for other reasons. Details on inclusion into the study have been published previously [14]. The final study cohort consisted of 178 patients. As seen in Table 2, the median age was 80 years (range, 70–94 years), and 57% were women. Almost all patients were living at home before surgery, and the majority (83%) were independent in IADL. However, comorbidities were common, with 74% of patients having moderate or serious comorbidity according to CIRS. Cognitive impairment was found in 7%, and malnutrition was found in 10%. Based on the GA data and the predefined cutoff values for each domain of the geriatric assessment, 76 patients (43%) were frail, and 102 (57%) were nonfrail. Fifty-two patients (29%) had rectal cancer. Eight patients had carcinoma in situ and were classified as TNM stage 0. A large majority had
OTncologist he
©AlphaMed Press 2014
®
Downloaded from http://theoncologist.alphamedpress.org/ at McMaster University on December 22, 2014
Age at time of surgery 70–79 years 80–89 years 901 years Sex Female Male Housing Private home Institution Tumor location Rectum Colon TNM stage 0 I II III IV Unclassified Surgery Open Laparoscopic Converted
Frail subgroup (n5 76)
Ommundsen, Wyller, Nesbakken et al.
1271
Association Between Frailty and Survival In frail and nonfrail patients, 1-year survival was 80% and 92%, respectively.The difference in survival increased further during the study period. In frail patients, 5-year survival was 24%, and median survival was 24 months. In nonfrail patients, 5-year survival was 66% (log rank p , .001) (Fig. 1). In univariate analysis, frailty, tumor stage, and sex were all prognostic factors for 5-year survival (Table 3). Age above 80 yearsas compared with age of 70–79 years was nota prognostic factor in the univariate analysis (Table 3) and was therefore not a part of the multivariable model. In multivariable Cox regression analysis, frailty status was a significant prognostic factor for survival when adjusting for TNM stage and sex, with a hazard ratio (HR) of 3.6 (95% confidence interval [CI] 2.3–5.5). Within the strata of localized and regional disease, 5-year survival was significantly higher in nonfrail than in frail patients (Fig. 2), with log-rank p value of ,0.001 in localized disease and of p 5 .007 in regional disease. In metastatic disease, mortality was high in both frail and nonfrail patients (log-rank p 5 .2).
Association Between Individual Frailty Indicators and 5-Year Survival We further analyzed the impact of the single components of the GA upon survival. In univariate analysis, comorbidity,
www.TheOncologist.com
nutritional status, cognitive function, polypharmacy, and IADL dependency were all prognostic factors for survival. Severe comorbidity and IADL dependency had the strongest associations with decreased survival, with a HR of 2.8 (1.8–4.3) and 2.8 (1.8–4.4), respectively.The only individual GA element that was not a significant prognostic factor for 5-year survival was depression (Table 4). In multivariable analysis correcting for TNM stage and sex, IADL function, comorbidity, and nutritional status remained individual prognostic factors for 5-year survival (Table 4). Because age had already been found to be without statistical significance in univariate analysis, we did not correct for age in this multivariable analysis.
DISCUSSION Our main finding was that frailty predicts both short-term (1year) and long-term (5-year) survival after elective surgery for colorectal cancer in older patients. The individual components of GA that were independently prognostic for survival were functional status (IADL), comorbidity, and nutritional status. As expected, TNM stage had a strong prognostic impact on survival, but the association between frailty and mortality remained pronounced within TNM stages 0–II, as well as within stage III. Of note, in tumor stages 0–II, only 28% of frail patients were alive after 5 years compared with 77% of nonfrail patients. In multivariable analysis, being frail (as opposed to nonfrail) implied a higher HR for mortality than having TNM stage III as opposed to stages 0–II. Thus, whereas tumor stage is essential for the prognosis and treatment of older patients with colorectal cancer, assessing frailty seems to be comparable in importance for evaluating overall prognosis in localized and regional disease. ©AlphaMed Press 2014
CME
potentially curable disease with 61% with TNM stages 0–II (localized disease), 25% with TNM stage III (regional disease), and only 12% with metastatic disease (TNM stage IV). During the first year after surgery, 23 patients (13%) died, and 93 (52%) died within 5 years after surgery. Median followup was 57.5 months (range, 1–60). There was no association between frailty and tumor stage: 43% of patients with localized disease, 40% of patients with regional disease and 48% of patients with distant metastases were frail.
Downloaded from http://theoncologist.alphamedpress.org/ at McMaster University on December 22, 2014
Figure 1. Five-year overall survival by frailty status. Kaplan-Meier plot of 5-year survival in frail (n 5 76) versus nonfrail (n 5 102) patients.
Frailty Predicts Survival in Colorectal Cancer
1272
Table 3. Predictive models for survival (Cox proportional hazards) with frailty and tumor stage Unadjusted models HR (95% CI)
p
HR (95% CI)
1a 1.2 (0.8–1.7)
.48
1a 1.6 (1.1–2.5)
.02
1a 1.5 (1.0–2.3)
p
.04
1a ,.001 1a ,.001 1.6 (1.0–2.6) 1.7 (1.0–2.7) 7.1 (4.1–12.3) 7.3 (4.1–13.0) 1a 3.3 (2.2–5.1)
,.001 1a 3.6 (2.3–5.5)
Downloaded from http://theoncologist.alphamedpress.org/ at McMaster University on December 22, 2014
Age 70–79 years .80 years Sex Female Male TNM stage 0–II III IV Frailty statusb Nonfrail Frail
Adjusted model
,.001
The table shows Cox proportional hazards model with univariate and multivariable analysis of frailty and tumor stage as predictors for 5-year survival. a Reference group. b For definition see text and Table 1. Abbreviations: CI, confidence interval; HR, hazard ratio; TNM, TNM classification of malignant tumors.
CME
Two recent reviews [16, 17] have summarized the prognostic properties of GA in older cancer patients. Puts et al. [17] found 13 prospective studies addressing the association between GA domains and mortality in different cancer groups. Although their conclusion is that the evidence so far is insufficient, most of the identified studies reported mental health, comorbidity, polypharmacy, malnutrition, and ADL impairments to be indicators of importance. Hamaker et al. [16] reviewed 25 studies and found comorbidity and malnutrition to be the most consistently reported risk factors for mortality. Our findings accord well with these reviews, but whereas they assessedtheimpactofGAdomains in a varietyofcancerpatients and thus found that the primary reports diverged in their conclusions, we provide data on the prognostic validity of GA in a well-defined homogeneous group of CRC patients. In a recent large study restricted to CRC patients, Gooiker et al. [26] likewise found comorbidity to be a profound risk factor for mortality during the first postoperative year, in addition to age, tumor stage, emergency surgery, and postoperative adverse events. Other GA components such as functional status were, however, not included in that study. Major strengths of our study are a prospective design with a long follow-up period, a standardized GA performed in the same preoperative setting of a truly aged population, and the fact that the same doctor performed all GAs. However, there are also weaknesses limiting the external validity of the results. The number of participants was limited, and they represent a selected group of patients who were referred to and accepted for elective surgery. Furthermore, the frailty assessment in these analyses did not include any physical performance measures such as gait speed. Recent studies have shown that clinical frailty scores that contain one or two physical performance measures have better predictive ability
Figure 2. Five-year survival in different tumor stages by frailty status. Kaplan-Meier plots of 5-year survival in frail versus nonfrail patients are stratified according to TNM classification of malignant tumors (TNM) stage. (A): TNM stages 0–II (localized disease; n 5 108; log rank p , .001). (B): TNM stage III (regional disease; n 5 45; log rank p 5 .007). (C): TNM stage IV (distant mestastases; n 5 21; log rank p 5 .2).
than those without [27]. In addition, cause of death is not reported. Further studies are warranted to explore whether frailty is of prognostic value for cancer-specific mortality in this population.
OTncologist he
©AlphaMed Press 2014
®
Ommundsen, Wyller, Nesbakken et al.
1273
Table 4. Predictive models for survival (Cox proportional hazards) with the individual frailty indicators
HR (95% CI)
p
HR (95% CI)
p
,.001
1a 1.6 (1.1–2.5)
.02
1a 1.6 (1.0–2.6) 7.1 (4.1–12.3)
,.001
1a 1.5 (0.9–2.5) 8.8 (4.9–15.7)
1a 2.8 (1.8–4.4)
,.001
1a 2.3 (1.3–4.0)
.006
1a 2.8 (1.8–4.3)
,.001
1a 1.9 (1.1–3.2)
.02
1a 2.2 (1.1–4.3)
.03
1a 2.3 (1.4–4.1)
.003
1a 1.8 (1.0–3.3)
.04
1a 2.2 (1.1–4.2)
.02
1a 1.4 (0.7–2.6)
.33
The table shows the Cox proportional hazards model with univariate and multivariable analysis of the individual frailty indicators and tumor stage as predictors for 5-year survival. An adjusted model was used with the following variables: sex, TNM stage, IADL function, comorbidity, number of systemic drugs, nutritional status, and cognitive function. a Reference group. b For definition, see Table 1. Abbreviations: CI, confidence interval; CIRS, Cumulative Illness Rating Scale; GDS, Geriatric Depression Scale; HR, hazard ratio; IADL, Instrumental activities of daily living; MMSE, Mini Mental State Evaluation; MNA, Mini Nutritional Assessment; NEADL, Nottingham Extended Activities of Daily Living Scale; TNM, TNM classification of malignant tumors.
Undertreatment and overtreatment are well-known pitfalls in geriatric oncology. Many of the patients are frail with limited remaining life expectancy. Understanding the heterogeneity of the aging process, in which some patients become frail while others remain fit and independent despite advanced chronological age, is of critical importance in prognostics and decision making.To avoid overtreatment, an essential question is whether the patient is going to live long enough to experience complications from his cancer disease [28]. In order to be able to answer this question, the treating physician needs knowledge of both the life expectancy of the patient and the expected progression of the cancer if left untreated.These are difficult tasks, and elements of uncertainty are almost always present. In our cohort, 93% of frail patients survived the first 3 months after surgery, and 80% of frail patients survived the first year. This may imply that overtreatment was not a major concern in our population. However, many older patients consider preserved physical and cognitive function after treatment to be more important than prolonged survival
www.TheOncologist.com
per se [29]. We have previously looked at physical function in a subsample of 84 patients from the same cohort. In that study, we found a significant reduction in ADL and IADL scores from the preoperative state until 16–28 months after surgery [30]. Approximately one-third of the patients had lost ADL function, while two-thirds had lost IADL function. Undertreatment of older cancer patients has been reported in several studies [31, 32], although there may have been some improvement in this field in recent years [33]. Undertreatment of colorectal cancer may give rise to serious and painful complications such as bleeding, bowel obstruction, and perforation. Emergency surgery carries a far higher risk than elective surgery [26], especially in older patients. Elective surgery is the preferred treatment, either for cure or for palliation, and after careful selection of patients [34, 35]. Despite recommendations, GA is still not fully incorporated into everyday clinical practice. One reason may be feasibility and time needed for the assessment. In our study, the assessment ©AlphaMed Press 2014
Downloaded from http://theoncologist.alphamedpress.org/ at McMaster University on December 22, 2014
Sex Female Male TNM stage 0–II III IV IADL function Independent (NEADL .43) Dependent (NEADL ,44) Comorbidity (CIRS) No/mild Severeb Systemic drugs ,8 .7 Nutritional status Normal (MNA .16) Malnourished (MNA ,17) Cognitive function Normal (MMSE .23) Reduced (MMSE ,24) Depression Not depressed (GDS ,14) Depressed (GDS .13)
Adjusted model
CME
Unadjusted models
Frailty Predicts Survival in Colorectal Cancer
1274
CONCLUSION Our study provides evidence on the prognostic value of GAbased frailty in older cancer patients. Geriatric assessment adds information about patient’s short-term and long-term overall survival, which, along with information of tumor stage at diagnosis, is of critical importance for decision making in older cancer patients. Performing a GA in older cancer patients
is recommended by the SIOG but is not yet fully incorporated into everyday clinical practice. For future research, emphasis should be on patient-centered outcomes such as cognitive and physical function and self-reported health. In addition, because evidence from randomized controlled trials on the effects of GA is lacking, intervention studies are needed.
ACKNOWLEDGMENT Funding for this study was provided through a grant from the Norwegian Cancer Society.
AUTHOR CONTRIBUTIONS Conception/Design: Nina Ommundsen, Torgeir B. Wyller, Arild Nesbakken, Marit S. Jordhøy, Arne Bakka, Eva Skovlund, Siri Rostoft Provision of study material or patients: Arild Nesbakken, Arne Bakka Collection and/or assembly of data: Nina Ommundsen, Siri Rostoft Data analysis and interpretation: Nina Ommundsen, Torgeir B. Wyller, Arild Nesbakken, Marit S. Jordhøy, Eva Skovlund, Siri Rostoft Manuscript writing: Nina Ommundsen, Torgeir B. Wyller, Arild Nesbakken, Marit S. Jordhøy, Arne Bakka, Eva Skovlund, Siri Rostoft Final approval of manuscript: Nina Ommundsen, Torgeir B. Wyller, Arild Nesbakken, Marit S. Jordhøy, Arne Bakka, Eva Skovlund, Siri Rostoft
DISCLOSURES The authors indicated no financial relationships.
REFERENCES 1. Hurria A, Gupta S, Zauderer M et al. Developing a cancer-specific geriatric assessment: A feasibility study. Cancer 2005;104:1998–2005.
11. Alibhai SMH. Comprehensive geriatric assessment in older patients with cancer: Two steps forward? J Geriatr Oncol 2013;4:205–207.
2. Parkin DM, Bray F, Ferlay J et al. Global cancer statistics, 2002. CA Cancer J Clin 2005;55:74–108.
12. Balducci L, Extermann M. Management of cancer in the older person: A practical approach.The Oncologist 2000;5:224–237.
3. Cancer Registry of Norway. Cancer in Norway 2010: Cancer Incidence, Mortality, Survival and Prevalence in Norway. Oslo, Norway: Cancer Registry of Norway, 2012. 4. Brenner H, Bouvier AM, Foschi R et al. Progress in colorectal cancer survival in Europe from the late 1980s to the early 21st century: The EUROCARE study. Int J Cancer 2012;131: 1649–1658. 5. Angell-Andersen E, Tretli S, Coleman MP et al. Colorectal cancer survival trends in Norway 1958–1997. Eur J Cancer 2004;40:734–742. 6. Morris EJA, Sandin F, Lambert PC et al. A population-based comparison of the survival of patients with colorectal cancer in England, Norway and Sweden between 1996 and 2004. Gut 2011;60: 1087–1093. 7. Nedrebø BS, Søreide K, Eriksen MT et al. Survival effect of implementing national treatment strategies for curatively resected colonic and rectal cancer. Br J Surg 2011;98:716–723. 8. Hari DM, Leung AM, Lee J-H et al. AJCC cancer staging manual 7th edition criteria for colon cancer: Do the complex modifications improve prognostic assessment? J Am Coll Surg 2013;217: 181–190.
CME
9. Wildiers H, Heeren P, Puts M et al. International society of geriatric oncology consensus on geriatric assessment in older patients with cancer. J Clin Oncol 2014;32:2595–2603. 10. Ellis G, Whitehead MA, O’Neill D et al. Comprehensive geriatric assessment for older adults admitted to hospital. Cochrane Database Syst Rev 2011;CD006211.
13. Clough-Gorr KM, Stuck AE,Thwin SS et al. Older breast cancer survivors: Geriatric assessment domains are associated with poor tolerance of treatment adverse effects and predict mortality over 7 years of follow-up. J Clin Oncol 2010;28: 380–386. 14. Kristjansson SR, Nesbakken A, Jordhøy MS et al. Comprehensive geriatric assessment can predict complications in elderly patients after elective surgery for colorectal cancer: A prospective observational cohort study. Crit Rev Oncol Hematol 2010;76:208–217. 15. Extermann M, Meyer J, McGinnis M et al. A comprehensive geriatric intervention detects multiple problems in older breast cancer patients. Crit Rev Oncol Hematol 2004;49:69–75. 16. Hamaker ME,Vos AG, Smorenburg CH et al.The value of geriatric assessments in predicting treatment tolerance and all-cause mortality in older patients with cancer. The Oncologist 2012;17: 1439–1449.
Illness Rating Scale. Psychiatry Res 1992;41:237– 248. 21. Salvi F, Miller MD, Grilli A et al. A manual of guidelines to score the modified cumulative illness rating scale and its validation in acute hospitalized elderly patients. J Am Geriatr Soc 2008;56:1926– 1931. 22. Guigoz Y. The mini nutritional assessment (MNA) review of the literature–what does it tell us? J Nutr Health Aging 2006;10:466–485. 23. Folstein MF, Folstein SE, McHugh PR. “Minimental state”: A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12:189–198. 24. Yesavage JA, Brink TL, Rose TL et al. Development and validation of a geriatric depression screening scale: A preliminary report. J Psychiatr Res 1982–1983;17:37–49. 25. Brink TL, Yesavage JA, Lum O et al. Screening tests for geriatric depression. Clin Gerontol 1982;1: 37–43. 26. Gooiker GA, Dekker JW, Bastiaannet E et al. Risk factors for excess mortality in the first year after curative surgery for colorectal cancer. Ann Surg Oncol 2012;19:2428–2434.
17. Puts MTE, Hardt J, Monette J et al. Use of geriatric assessment for older adults in the oncology setting: A systematic review. J Natl Cancer Inst 2012; 104:1133–1163.
27. Woo J, Leung J, Morley JE. Comparison of frailty indicators based on clinical phenotype and the multiple deficit approach in predicting mortality and physical limitation. J Am Geriatr Soc 2012;60: 1478–1486.
18. Mahoney FI, Barthel DW. Functional evaluation: The Barthel index. Md State Med J 1965;14: 61–65.
28. Balducci L, Colloca G, Cesari M et al. Assessment and treatment of elderly patients with cancer. Surg Oncol 2010;19:117–123.
19. Lincoln NB, Gladman JRF. The Extended Activities of Daily Living Scale: A further validation. Disabil Rehabil 1992;14:41–43.
29. Fried TR, Bradley EH, Towle VR et al. Understanding the treatment preferences of seriously ill patients. N Engl J Med 2002;346: 1061–1066.
20. Miller MD, Paradis CF, Houck PR et al. Rating chronic medical illness burden in geropsychiatric practice and research: Application of the Cumulative
30. Rønning B, Wyller TB, Jordhøy MS et al. Frailty indicators and functional status in older patients
OTncologist he
©AlphaMed Press 2014
®
Downloaded from http://theoncologist.alphamedpress.org/ at McMaster University on December 22, 2014
took 20–60 minutes per patient. To reduce the time needed for the assessment, one might wish to exclude some of its domains and assess only those with the strongest predictive power. In our study, these were comorbidity, functional status, and nutritional status. However, the evidence regarding the predictive value of individual domains of the GA is still inconsistent [16]. In addition, some domains have obvious clinical value irrespective of predictive power. For example, it is essential to discover cognitive dysfunction in a patient prior to discussing consent and when providing treatment that requires the patient to be alert of possible complications. Depression in older cancer patients is prevalent, causes considerable morbidity and suffering, and can be treated [36]. Polypharmacy is a large and increasing problem in the older population, causing considerable morbidity and mortality [37].Therefore, a full GA is still recommended.
Ommundsen, Wyller, Nesbakken et al.
1275
after colorectal cancer surgery. J Geriatr Oncol 2014; 5:26–32.
cancer in South Netherlands, 1995 to 2002. Cancer 2006;106:2734–2742.
31. Van Leeuwen BL, Rosenkranz KM, Feng LL et al. The effect of under-treatment of breast cancer in women 80 years of age and older. Crit Rev Oncol Hematol 2011;79:315–320.
33. Bernardi D, Errante D,Tirelli U et al. Insight into the treatment of cancer in older patients: Developments in the last decade. Cancer Treat Rev 2006;32: 277–288. 34. Simmonds PD, Best L, George S et al. Surgery for colorectal cancer in elderly patients: A systematic review. Lancet 2000;356:968– 974.
32. Vulto AJ, Lemmens VE, Louwman MW et al.The influence of age and comorbidity on receiving radiotherapy as part of primary treatment for
CME
35. Kunitake H, Zingmond DS, Ryoo J et al. Caring for octogenarian and nonagenarian patients with colorectal cancer: What should our standards and expectations be? Dis Colon Rectum 2010;53:735–743. 36. Mottram P, Wilson K, Strobl J. Antidepressants for depressed elderly. Cochrane Database Syst Rev 2006;CD003491. 37. Hajjar ER, Cafiero AC, Hanlon JT. Polypharmacy in elderly patients. Am J Geriatr Pharmacother 2007; 5:345–351.
This article is available for continuing medical education credit at CME.TheOncologist.com.
CME
Implications for Practice: This article explains how to conduct a geriatric assessment, how to implement it into clinical practice, and how to use the results of the assessment in clinical oncology practice. Furthermore, information is provided about available resources on geriatric assessment as well as geriatric assessment and screening tools, and important challenges of implementing geriatric assessment in practice are highlighted.
Downloaded from http://theoncologist.alphamedpress.org/ at McMaster University on December 22, 2014
For Further Reading: Schroder Sattar, Shabbir M.H. Alibhai, Hans Wildiers et al. How to Implement a Geriatric Assessment in Your Clinical Practice. The Oncologist 2014;19:1056–1068.
www.TheOncologist.com
©AlphaMed Press 2014
References
This article cites 34 articles, 5 of which you can access for free at: http://theoncologist.alphamedpress.org/content/19/12/1268.full.html#ref-list-1
Downloaded from http://theoncologist.alphamedpress.org/ at McMaster University on December 22, 2014
Frailty Is an Independent Predictor of Survival in Older Patients With Colorectal Cancer Nina Ommundsen, Torgeir B. Wyller, Arild Nesbakken, Marit S. Jordhøy, Arne Bakka, Eva Skovlund and Siri Rostoft The Oncologist 2014, 19:1268-1275. doi: 10.1634/theoncologist.2014-0237 originally published online October 29, 2014
Downloaded from http://theoncologist.alphamedpress.org/ at McMaster University on December 22, 2014
The online version of this article, along with updated information and services, is located on the World Wide Web at: http://theoncologist.alphamedpress.org/content/19/12/1268
