letters to the editor
Annals of Oncology
3. Puhaindran ME, Farooki A, Steensma MR et al. Atypical subtrochanteric femoral fractures in patients with skeletal malignant involvement treated with intravenous bisphosphonates. J Bone Joint Surg Am 2011; 93: 1235–1242. 4. Chang ST, Tenforde AS, Grimsrud CD et al. Atypical femur fractures among breast cancer and multiple myeloma patients receiving intravenous bisphosphonate therapy. Bone 2012; 51: 524–527.
doi: 10.1093/annonc/mdv014 Published online 20 January 2015
Reply to the letter to the editor ‘Albumin to globulin ratio, a predictor or a misleader?’ by Alkan et al.
older than 60, as well as subjects with previous history of major rheumatic diseases, including rheumatic arthritis (ICD-10 M05), systemic lupus erythematosis (M32), ankylosing spondylitis (M45), systemic sclerosis (M34), dermatopolymyositis (M33), other connective tissue disease (M35–M36), as well as Crohn’s disease (K50), and ulcerative colitis (K51). The study population thus decreased from 26 974 to 20 695 subjects. The results are shown in Table 1. As expected, event numbers have significantly decreased (∼70%) but the overall trend is shown to be apparently intact, with adjusted hazard ratios remaining similar in general throughout all AGR groups. Overall, the association between low AGR and cancer is a legitimate observation, although its clinical application remains undetermined, deserving elucidation by future studies. B. Suh1, S. Park2 & D. W. Shin1,3* 1
We appreciate the letter to the editor by Alkan et al. [1] in response to our recently published article [2]. Alkan et al. bring up some potentially valid points about our study. They suggest rheumatic diseases should have been excluded from the study population, as these conditions are ‘important causatives for chronic inflammation.’ They also suggest the inclusion of elderly subjects older than 60, comprising 24.2% of the study population, may be misleading to the results, as these subjects are ‘prone to malnutrition and also hypoalbuminemia.’ In order to address these suggestions, we have investigated the association of low albumin-to-globulin ratio (AGR) with cancer after having further excluded (in addition to the exclusion criteria originally implemented in our study) elderly subjects
Department of Family Medicine and Health Promotion Center Division of Hematology and Medical Oncology, Department of Internal Medicine, Seoul National University Hospital, Seoul 3 Cancer Survivorship Clinic, Seoul National University Cancer Hospital, Seoul, Republic of Korea (*E-mail: [email protected]) 2
disclosure The authors have declared no conflicts of interest.
references 1. Alkan A, Köksoy E, Utkan G. Albumin to globulin ratio, a predictor or a misleader? Ann Oncol 2015; 25: 443–444.
Table 1. Cox proportional hazards models for mortality and cancer incidence before and after revision in study population
All-cause mortality AGR ≥1.5 1.5> AGR ≥1.2 1.2> AGR ≥1.1 1.1> AGR ≥1.0 1.0> AGR Cancer mortality AGR ≥1.5 1.5> AGR ≥1.2 1.2> AGR ≥1.1 1.1> AGR ≥1.0 1.0> AGR Cancer incidence AGR ≥1.5 1.5> AGR ≥1.2 1.2> AGR ≥1.1 1.1> AGR ≥1.0 1.0> AGR
Before N (%)
Event no.
Ratea
aHRb (95% CI)
After N (%)
12 356 (45.8) 12 599 (46.7) 1519 (5.6) 395 (1.5) 105 (0.4)
81 175 34 15 11
1.41 2.25 3.03 5.08 15.28
1 1.34 (1.03–1.76) 1.61 (1.07–2.43) 2.69 (1.54–4.72) 6.71 (3.56–12.66)
1 1.29 (0.88–1.89) 1.67 (0.87–3.21) 3.19 (1.34–7.57) 7.84 (2.80–21.95)
9918 (47.9) 9407 (45.5) 1038 (5.0) 265 (1.3) 67 (0.3)
45 74 12 6 4
0.97 1.25 1.54 2.99 8.34
12 356 (45.8) 12 599 (46.7) 1519 (5.6) 395 (1.5) 105 (0.4)
44 87 17 9 4
0.77 1.12 1.52 3.05 5.55
1 1.24 (0.86–1.80) 1.49 (0.84–2.64) 2.95 (1.42–6.11) 4.38 (1.57–12.25)
1 1.26 (0.74–2.13) 1.72 (0.72–4.10) 4.49 (1.67–12.03) 3.33 (0.45–24.82)
9918 (47.9) 9407 (45.5) 1038 (5.0) 265 (1.3) 67 (0.3)
23 40 7 5 1
0.49 0.68 0.90 2.49 2.08
12 356 (45.8) 12 599 (46.7) 1519 (5.6) 395 (1.5) 105 (0.4)
158 244 42 19 10
2.77 3.15 3.77 6.52 14.21
1 1.07 (0.87–1.31) 1.21 (0.85–1.72) 2.07 (1.28–3.36) 3.99 (2.10–7.58)
1 1.12 (0.87–1.46) 1.20 (0.74–1.94) 2.53 (1.37–4.65) 2.48 (0.78–7.86)
9918 (47.9) 9407 (45.5) 1038 (5.0) 265 (1.3) 67 (0.3)
101 152 21 12 3
2.18 2.58 2.70 6.08 6.33
Event no.
Ratea
a
Rate per 1000 person-year. Multivariable Cox proportional hazards models adjusted for age, sex, current smoking, body mass index, and previous history of chronic liver disease.
b
| letters to the editor
Volume 26 | No. 4 | April 2015
letters to the editor
Annals of Oncology 2. Suh B, Park S, Shin DW et al. Low albumin-to-globulin ratio associated with cancer incidence and mortality in generally healthy adults. Ann Oncol 2014; 25: 2260–2266.
doi: 10.1093/annonc/mdv006 Published online 18 January 2015
Obesity and cancer: links with survival differ from those with incidence The letter from Bifulco in the Annals of Oncology [1], prompted by the recently published data from the POSH study [2], gives a refreshing update on the link between obesity and cancer, and emphasises the need for continued research to understand the underpinning molecular mechanisms in a cancer-specific framework. However, for the readership unfamiliar with the field of ‘adiponcosis’, one might mistakenly think that the negative impacts of obesity on cancer risk are paralleled by adverse influences of obesity on treatment outcome. There is a large volume of epidemiological data that excess weight [commonly approximated as body mass index (BMI)] is associated with increased incident risk for several common adult cancer types. Given the consistency, strengths, and specificities of associations; the sufficiently long latency times between BMI measurements and cancer occurrence (typically >8 years); and reversibility 10 years and more after bariatric surgery; many of these associations are probably causal. For 2012, the estimated attributable risk due to high BMI worldwide was 3.6% of all incident cancers, or almost half a million new cancers [3]—in other words, this is globally a substantial public health problem. In contrast, the evidence that excess weight, either at the time of cancer diagnosis or in the survivorship period sometime after cancer diagnosis, influences either overall or cancer-specific survivals is far from clear. For breast cancer, the tumour type with the greatest volume of evidence, the World Cancer Research Fund (WCRF) recently undertook a comprehensive review of this question, including up to 49 studies totally 16 000 deaths (varied by analysis type) [4]. The report emphasized that, while there are many studies reporting an adverse impact of excess weight on survival, interpretation of the majority of studies is limited by biases and confounding. In relation to breast cancer mortality, the report concluded that ‘the evidence suggesting that greater body fatness before, or less than 12 months after a diagnosis of postmenopausal primary breast cancer increases risk is limited’. The POSH study [2], published since the WCRF
Volume 26 | No. 4 | April 2015
report, which shows that excess peri-diagnosis BMI is associated with a poorer survival in young women with ER-positive breast cancer, does not materially alter the WCRF conclusions. My research team have arrived at similar conclusions for colorectal cancer [5]; and after secondary analyses of randomised trial data (where patients receive standardised allocated treatments and therefore reduces biases), arrived at similar interpretations for endometrial cancer [6], a malignancy where risk is strongly linked with obesity. By extension, there are two clinical lessons here. First, there is an important epidemiological principle: that an established link between an exposure (here, body fatness) and increased incident cancer risk, does not necessarily translate into an inferior outcome following treatment of that cancer. Second, if a lifestyle factor is not causally linked with prognosis, it is unlikely that its modification during survivorship will impact significantly on oncological outcomes. A. G. Renehan* Diabetes Obesity and Cancer Research Group, Institute of Cancer Sciences, University of Manchester, Manchester, UK (*E-mail: [email protected])
disclosure The author has declared no conflicts of interest.
references 1. Bifulco M. The obesity and cancer link. Ann Oncol 2015; 26: 440–441. 2. Copson ER, Cutress RI, Maishman T et al. Obesity and the outcome of young breast cancer patients in the UK: the POSH study. Ann Oncol 2015; 26: 101–112. 3. Arnold M, Pandeya N, Byrnes G et al. Global burden of cancer attributable to high body-mass index in 2012: a population-based study. Lancet Oncol 2014 Nov 26 [epub ahead of print], doi: 10.1016/S1470-2045(14)71123-4. 4. WCRF. World Cancer Research Fund International. Continuous Update Project Report: Diet, Nutrition, Physical Activity, and Breast Cancer Survivors. 2014. www.wcrf.org/sites/default/files/Breast-Cancer-Survivors-2014-Report.pdf (20 December 2014, date last accessed). 5. Parkin E, O’Reilly DA, Sherlock DJ, Manoharan P, Renehan AG. Excess adiposity and survival in patients with colorectal cancer: a systematic review. Obes Rev 2014; 15: 434–451. 6. Crosbie EJ, Roberts C, Qian W et al. Body mass index does not influence posttreatment survival in early stage endometrial cancer: results from the MRC ASTEC trial. Eur J Cancer 2012; 48: 853–864.
doi: 10.1093/annonc/mdv016 Published online 20 January 2015
doi:10.1093/annonc/mdv016 |
Copyright of Annals of Oncology is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
Annals of Oncology
3. Puhaindran ME, Farooki A, Steensma MR et al. Atypical subtrochanteric femoral fractures in patients with skeletal malignant involvement treated with intravenous bisphosphonates. J Bone Joint Surg Am 2011; 93: 1235–1242. 4. Chang ST, Tenforde AS, Grimsrud CD et al. Atypical femur fractures among breast cancer and multiple myeloma patients receiving intravenous bisphosphonate therapy. Bone 2012; 51: 524–527.
doi: 10.1093/annonc/mdv014 Published online 20 January 2015
Reply to the letter to the editor ‘Albumin to globulin ratio, a predictor or a misleader?’ by Alkan et al.
older than 60, as well as subjects with previous history of major rheumatic diseases, including rheumatic arthritis (ICD-10 M05), systemic lupus erythematosis (M32), ankylosing spondylitis (M45), systemic sclerosis (M34), dermatopolymyositis (M33), other connective tissue disease (M35–M36), as well as Crohn’s disease (K50), and ulcerative colitis (K51). The study population thus decreased from 26 974 to 20 695 subjects. The results are shown in Table 1. As expected, event numbers have significantly decreased (∼70%) but the overall trend is shown to be apparently intact, with adjusted hazard ratios remaining similar in general throughout all AGR groups. Overall, the association between low AGR and cancer is a legitimate observation, although its clinical application remains undetermined, deserving elucidation by future studies. B. Suh1, S. Park2 & D. W. Shin1,3* 1
We appreciate the letter to the editor by Alkan et al. [1] in response to our recently published article [2]. Alkan et al. bring up some potentially valid points about our study. They suggest rheumatic diseases should have been excluded from the study population, as these conditions are ‘important causatives for chronic inflammation.’ They also suggest the inclusion of elderly subjects older than 60, comprising 24.2% of the study population, may be misleading to the results, as these subjects are ‘prone to malnutrition and also hypoalbuminemia.’ In order to address these suggestions, we have investigated the association of low albumin-to-globulin ratio (AGR) with cancer after having further excluded (in addition to the exclusion criteria originally implemented in our study) elderly subjects
Department of Family Medicine and Health Promotion Center Division of Hematology and Medical Oncology, Department of Internal Medicine, Seoul National University Hospital, Seoul 3 Cancer Survivorship Clinic, Seoul National University Cancer Hospital, Seoul, Republic of Korea (*E-mail: [email protected]) 2
disclosure The authors have declared no conflicts of interest.
references 1. Alkan A, Köksoy E, Utkan G. Albumin to globulin ratio, a predictor or a misleader? Ann Oncol 2015; 25: 443–444.
Table 1. Cox proportional hazards models for mortality and cancer incidence before and after revision in study population
All-cause mortality AGR ≥1.5 1.5> AGR ≥1.2 1.2> AGR ≥1.1 1.1> AGR ≥1.0 1.0> AGR Cancer mortality AGR ≥1.5 1.5> AGR ≥1.2 1.2> AGR ≥1.1 1.1> AGR ≥1.0 1.0> AGR Cancer incidence AGR ≥1.5 1.5> AGR ≥1.2 1.2> AGR ≥1.1 1.1> AGR ≥1.0 1.0> AGR
Before N (%)
Event no.
Ratea
aHRb (95% CI)
After N (%)
12 356 (45.8) 12 599 (46.7) 1519 (5.6) 395 (1.5) 105 (0.4)
81 175 34 15 11
1.41 2.25 3.03 5.08 15.28
1 1.34 (1.03–1.76) 1.61 (1.07–2.43) 2.69 (1.54–4.72) 6.71 (3.56–12.66)
1 1.29 (0.88–1.89) 1.67 (0.87–3.21) 3.19 (1.34–7.57) 7.84 (2.80–21.95)
9918 (47.9) 9407 (45.5) 1038 (5.0) 265 (1.3) 67 (0.3)
45 74 12 6 4
0.97 1.25 1.54 2.99 8.34
12 356 (45.8) 12 599 (46.7) 1519 (5.6) 395 (1.5) 105 (0.4)
44 87 17 9 4
0.77 1.12 1.52 3.05 5.55
1 1.24 (0.86–1.80) 1.49 (0.84–2.64) 2.95 (1.42–6.11) 4.38 (1.57–12.25)
1 1.26 (0.74–2.13) 1.72 (0.72–4.10) 4.49 (1.67–12.03) 3.33 (0.45–24.82)
9918 (47.9) 9407 (45.5) 1038 (5.0) 265 (1.3) 67 (0.3)
23 40 7 5 1
0.49 0.68 0.90 2.49 2.08
12 356 (45.8) 12 599 (46.7) 1519 (5.6) 395 (1.5) 105 (0.4)
158 244 42 19 10
2.77 3.15 3.77 6.52 14.21
1 1.07 (0.87–1.31) 1.21 (0.85–1.72) 2.07 (1.28–3.36) 3.99 (2.10–7.58)
1 1.12 (0.87–1.46) 1.20 (0.74–1.94) 2.53 (1.37–4.65) 2.48 (0.78–7.86)
9918 (47.9) 9407 (45.5) 1038 (5.0) 265 (1.3) 67 (0.3)
101 152 21 12 3
2.18 2.58 2.70 6.08 6.33
Event no.
Ratea
a
Rate per 1000 person-year. Multivariable Cox proportional hazards models adjusted for age, sex, current smoking, body mass index, and previous history of chronic liver disease.
b
| letters to the editor
Volume 26 | No. 4 | April 2015
letters to the editor
Annals of Oncology 2. Suh B, Park S, Shin DW et al. Low albumin-to-globulin ratio associated with cancer incidence and mortality in generally healthy adults. Ann Oncol 2014; 25: 2260–2266.
doi: 10.1093/annonc/mdv006 Published online 18 January 2015
Obesity and cancer: links with survival differ from those with incidence The letter from Bifulco in the Annals of Oncology [1], prompted by the recently published data from the POSH study [2], gives a refreshing update on the link between obesity and cancer, and emphasises the need for continued research to understand the underpinning molecular mechanisms in a cancer-specific framework. However, for the readership unfamiliar with the field of ‘adiponcosis’, one might mistakenly think that the negative impacts of obesity on cancer risk are paralleled by adverse influences of obesity on treatment outcome. There is a large volume of epidemiological data that excess weight [commonly approximated as body mass index (BMI)] is associated with increased incident risk for several common adult cancer types. Given the consistency, strengths, and specificities of associations; the sufficiently long latency times between BMI measurements and cancer occurrence (typically >8 years); and reversibility 10 years and more after bariatric surgery; many of these associations are probably causal. For 2012, the estimated attributable risk due to high BMI worldwide was 3.6% of all incident cancers, or almost half a million new cancers [3]—in other words, this is globally a substantial public health problem. In contrast, the evidence that excess weight, either at the time of cancer diagnosis or in the survivorship period sometime after cancer diagnosis, influences either overall or cancer-specific survivals is far from clear. For breast cancer, the tumour type with the greatest volume of evidence, the World Cancer Research Fund (WCRF) recently undertook a comprehensive review of this question, including up to 49 studies totally 16 000 deaths (varied by analysis type) [4]. The report emphasized that, while there are many studies reporting an adverse impact of excess weight on survival, interpretation of the majority of studies is limited by biases and confounding. In relation to breast cancer mortality, the report concluded that ‘the evidence suggesting that greater body fatness before, or less than 12 months after a diagnosis of postmenopausal primary breast cancer increases risk is limited’. The POSH study [2], published since the WCRF
Volume 26 | No. 4 | April 2015
report, which shows that excess peri-diagnosis BMI is associated with a poorer survival in young women with ER-positive breast cancer, does not materially alter the WCRF conclusions. My research team have arrived at similar conclusions for colorectal cancer [5]; and after secondary analyses of randomised trial data (where patients receive standardised allocated treatments and therefore reduces biases), arrived at similar interpretations for endometrial cancer [6], a malignancy where risk is strongly linked with obesity. By extension, there are two clinical lessons here. First, there is an important epidemiological principle: that an established link between an exposure (here, body fatness) and increased incident cancer risk, does not necessarily translate into an inferior outcome following treatment of that cancer. Second, if a lifestyle factor is not causally linked with prognosis, it is unlikely that its modification during survivorship will impact significantly on oncological outcomes. A. G. Renehan* Diabetes Obesity and Cancer Research Group, Institute of Cancer Sciences, University of Manchester, Manchester, UK (*E-mail: [email protected])
disclosure The author has declared no conflicts of interest.
references 1. Bifulco M. The obesity and cancer link. Ann Oncol 2015; 26: 440–441. 2. Copson ER, Cutress RI, Maishman T et al. Obesity and the outcome of young breast cancer patients in the UK: the POSH study. Ann Oncol 2015; 26: 101–112. 3. Arnold M, Pandeya N, Byrnes G et al. Global burden of cancer attributable to high body-mass index in 2012: a population-based study. Lancet Oncol 2014 Nov 26 [epub ahead of print], doi: 10.1016/S1470-2045(14)71123-4. 4. WCRF. World Cancer Research Fund International. Continuous Update Project Report: Diet, Nutrition, Physical Activity, and Breast Cancer Survivors. 2014. www.wcrf.org/sites/default/files/Breast-Cancer-Survivors-2014-Report.pdf (20 December 2014, date last accessed). 5. Parkin E, O’Reilly DA, Sherlock DJ, Manoharan P, Renehan AG. Excess adiposity and survival in patients with colorectal cancer: a systematic review. Obes Rev 2014; 15: 434–451. 6. Crosbie EJ, Roberts C, Qian W et al. Body mass index does not influence posttreatment survival in early stage endometrial cancer: results from the MRC ASTEC trial. Eur J Cancer 2012; 48: 853–864.
doi: 10.1093/annonc/mdv016 Published online 20 January 2015
doi:10.1093/annonc/mdv016 |
Copyright of Annals of Oncology is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
