Accepted Manuscript Symptom Burden of Cancer Patients: Validation of the German M. D. Anderson Symptom Inventory. A Cross-Sectional Multicenter Study Heike Schmidt , MD Charles S. Cleeland , PhD Alexander Bauer , PhD Margarete Landenberger , PhD Patrick Jahn , RN, PhD PII:
S0885-3924(14)00255-3
DOI:
10.1016/j.jpainsymman.2014.04.007
Reference:
JPS 8673
To appear in:
Journal of Pain and Symptom Management
Received Date: 6 August 2013 Revised Date:
11 April 2014
Accepted Date: 29 April 2014
Please cite this article as: Schmidt H, Cleeland CS, Bauer A, Landenberger M, Jahn P, Symptom Burden of Cancer Patients: Validation of the German M. D. Anderson Symptom Inventory. A CrossSectional Multicenter Study, Journal of Pain and Symptom Management (2014), doi: 10.1016/ j.jpainsymman.2014.04.007. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Brief Methodological Report
13-00438R1
Symptom Burden of Cancer Patients: Validation of the German M. D. Anderson Symptom
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Inventory. A Cross-Sectional Multicenter Study
Heike Schmidt, MD, Charles S. Cleeland, PhD, Alexander Bauer, PhD, Margarete
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Landenberger, PhD, and Patrick Jahn, RN, PhD
Institute for Health and Nursing Science (H.S., A.B., M.L., P.J.), Medical Faculty, Martin Luther
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University Halle-Wittenberg, and University Hospital Halle (Saale) (P.J.), Halle, Germany; and Department of Symptom Research (C.S.), The University of Texas M. D. Anderson Cancer Center, Houston, Texas, USA
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Address correspondence to: Heike Schmidt, MD
Medical Faculty, Institute for Health and Nursing Science
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Martin-Luther-University Halle-Wittenberg, Magdeburger Strasse 8
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06097 Halle, Germany
E-mail: [email protected] AU: PLS CHECK ALL AUTHOR DEGREES
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Abstract Context. Cancer patients frequently suffer from various symptoms often impairing functional status and quality of life. To enable timely supportive care, these symptoms must be
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assessed adequately with reliable tools.
Objectives. This study aimed to validate the German version of the M. D. Anderson Symptom Inventory.
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Methods. This was a multicenter, cross-sectional, observational study. At five German university hospitals, 697 cancer patients aged from 18 to 80 years undergoing active anti-cancer
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treatment were recruited to participate in the study. For the validation, reliability (Cronbach’s alpha), construct validity (factor analysis), known group validity (ECOG PS) and convergent divergent analyses were calculated.
Results. Of 980 patients who were eligible, 697 patients were included and agreed to
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participate in the study (71%). Reliability analysis showed good internal consistencies for the MDASI set of symptom items (Cronbach’s alpha coefficient = 0.82, 95% CI: 0.78, 0.84) and for the set of interference items (Cronbach’s alpha coefficient =0.857, 95% CI: 0.484, 0.87). Factor
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analysis resulted in a one-factor solution (general symptoms) (eigenvalue 4.26) with a psychological (distress and sadness) and a gastrointestinal subscale (nausea and vomiting).
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Convergent and divergent analysis showed significant correlations between symptom burden and distress and global health-related quality of life (subscale of the EORTC QLQ-C30 v. 3.0.). Conclusion. The MDASI-G is a valid tool for measuring patient reported symptom severity and symptom interference in German cancer patients. It is easily applicable and can be used by German clinicians and researchers for screening and monitoring purposes and the comparison of international data. ClinicalTrials.gov Identifier: NCT 01317355
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Key Words Cancer, symptom burden, validation, M. D. Anderson Symptom Inventory Running title: Validation of the MDASI-G
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Accepted for publication: April 29, 2014.
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Introduction Cancer patients often suffer from various disease- or treatment-related symptoms that may impair their functional status and result in high symptom burden. Unrelieved symptoms can
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limit therapy options and reduce quality of life [1]. In clinical practice, symptoms might persist unrecognized and undertreated because, when not asked, patients might not report their
symptoms exhaustively. Furthermore considerable numbers of clinicians underestimate symptom
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intensity [2, 3]. Therefore, in order to enable tailored supportive care measures, all relevant symptoms have to be assessed correctly and frequently including the patients’ perceptions.
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Patient-reported outcomes (PRO) are more and more accepted as significant measures of symptom intensity and interference as well as of health-related quality of life [1, 4-6]. However, comprehensive standardized assessments are still not widely used in daily clinical practice despite the many available and valid questionnaires. To facilitate implementation of PRO
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measures in everyday practice, it is important to provide valid but also feasible questionnaires that assess relevant symptoms [7].
The M. D. Anderson Symptom Inventory (MDASI) is a comparatively short self-
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administered questionnaire that was developed and validated to measure symptom intensity and interference in cancer patients [1]. It comprises 19 numeric rating scales (NRSs) regarding
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presence and intensity of common symptoms and functional restrictions. The MDASI assesses the severity of 13 symptoms at their worst in the last 24 hours on a 0–10 NRS, with 0 being “not present” and 10 being “as bad as you can imagine [1]. The symptom scales represent two underlying structures: a general symptom severity factor (pain, fatigue, disturbed sleep, distress (emotional), shortness of breath, drowsiness, dry mouth, sadness, difficulty remembering, and numbness or tingling) and a gastrointestinal factor (nausea and vomiting); lack of appetite loads
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on both factors [1]. A component score of symptom severity can be calculated by taking the average of the 13 items together [19]. Symptom interference with daily activities is measured by six functional scales regarding general activity, mood, work, relations with others, walking, and
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enjoyment of life. Interference is also rated on a 0–10 NRS, 0 being “did not interfere” and 10 being “interfered completely.” The mean of the interference items can be used to represent overall symptom distress. Symptom burden is defined as the sum of symptom severity and
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symptom interference [19].
Because scores of single items can be directly understood and implied in daily care
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without further computing, the MDASI can be used easily to screen or to monitor symptoms throughout the course of the treatment. It has been translated and validated in many languages including French, Taiwanese and Russian [8-15].
The main objective of this study was to gather representative information about symptom
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severity, symptom interference and symptom burden within a large heterogeneous population of cancer patients undergoing active anti-cancer treatment in different settings. In order to test and provide a relatively short disease-specific instrument with a short recall period feasible for
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screening and monitoring for future use in clinical routine, we decided to use the German version of the MDASI (MDASI-G), which already has been linguistically validated, and to perform a
Methods
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psychometric validation of this tool.
Study Design
The study was designed as a multicenter, cross-sectional, observational study to investigate symptom severity and symptom interference in a heterogeneous population of cancer patients in different settings. The validation study was carried out alongside the large descriptive
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study. Recruitment took place at the oncology departments of five German university hospitals and aimed to fulfill convenience samples of n=150 inpatients and outpatients per center. Participants
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Inclusion Criteria. Patients between 18 and 80 years of age, diagnosed with cancer and undergoing active anti-cancer treatment with an Eastern Cooperative Oncology Group
Performance Status (ECOG PS) of ≤3 who gave written informed consent were eligible to
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participate in the study.
Exclusion Criterion. Patients lacking sufficient knowledge of the German language were
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not eligible. Data Sources
To perform the psychometric validation, we used the linguistically validated MDASI-G provided by the M. D. Anderson Cancer Center. In addition, patients filled out the Distress
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Thermometer (DT), which is a short screening tool for measuring self-reported distress on a 0-10 NRS [16], and the two general questions of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-C30 (EORTC QLQ-C30), v. 3.0, regarding
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global health-related quality of life [17]. Demographic and disease-related data (age, gender,
collected.
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marital status, education level, disease type, model of care and type of treatment) also were
Ethical Considerations
As study data were not available for the physicians treating the participants, there was no direct advantage, e.g. application of supportive measures, for the participants. To reduce the burden on the patients, we limited the number of items to be answered and did not use the problem check list of the DT or another comparable reference questionnaire assessing symptoms
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and functional impairments. Patients who were not willing to participate also did not give permission to save any data. Therefore, reasons for non-participation could not be elicited. The study was approved by the local ethics committees of the participating university hospitals.
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Statistical Analysis
Scoring of the symptom severity and symptom interference scales including the handling of missing values was carried out as described in the MDASI User Guide [19]. Descriptive
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statistics were used to give an account of symptom prevalence, severity and interference. In accordance with the methodology used in the original English language validation study and
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studies validating the MDASI for foreign languages, our validation analysis plan included examination of reliability, known-group validity and analysis of convergence and divergence. To establish reliability, we examined the internal consistency (Cronbach’s alpha coefficient). To establish convergent validity, we performed a convergent and divergent analysis by testing the
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correlation of symptom burden (sum of the means of symptom severity and symptom interference) with distress (DT) and global health-related quality of life (EORTC QLQ-C30 global scale). To examine the underlying constructs that the MDASI-G is supposed to measure,
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we performed an exploratory factor analysis (EFA) on our validation sample. Because other language versions of the MDASI showed various factor solutions [1, 8, 11, 12, 14, 15], we chose
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EFA over confirmatory factor analysis (CFA) to better understand the constructs being assessed by the MDASI-G. All analyses were carried out using SPSS v. 18 (SPSS Inc. Chicago, IL). Results
Participants
Of the 980 patients who were eligible, 697 patients were included and agreed to participate in the study (71%). Recruitment sites were internal medicine (n=268, 38.5%),
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gynecology (n=146, 20.9%), surgery (n=104, 14.9%) radiotherapy (n=93, 13.3%), urology (n=58, 8.3%) head and neck (n=19, 2.7%) and dermatology (n=7, 1.0%) wards. Recruitment rates are shown in Table 1; demographic and disease-related data are shown in Table 2. As non-
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participants did not give permission to collect any data, the reasons for non-participation could not be examined. Descriptive Analyses of the MDASI-G
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Descriptive analyses were performed following the instructions given in the MDASI user guide [19]. Eleven patients did not complete the required seven items of symptom severity and
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two patients did not complete the required four items of symptom interference. Following the National Comprehensive Cancer Network guidelines for the assessment of pain [20] and the original validation study [1], we defined symptom severity as mild if it was rated between 1 and 3, moderate if it was rated between 4 and 6 and severe if it was rated equal
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or greater than 7 on the 0-10 NRS. Descriptive results for means, symptom prevalence and severity are presented in Table 3. Statistical Analyses
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Reliability. We examined internal consistency by calculating the Cronbach’s alpha coefficient. Following the rule of thumb by George and Mallery, alpha values >0.9 are rated
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excellent, > 0.8 good, >0.7 acceptable and values < 0.6 doubtful [21]. Analysis showed good internal consistencies for the MDASI set of symptom items (Cronbach’s alpha coefficient = 0.82, 95% CI: 0.80, 0.84) and for the set of interference items (Cronbach’s alpha coefficient =0.84, 95% CI: 0.82, 0.86) (Table 3). Construct Validity. Construct validity was assessed by factor analysis regarding the symptom scales. The data were suitable for factor analysis (Kaiser-Mayer-Olkin criterion: 0.80).
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The correlation matrix with Z-standardized values showed highest correlations between distress and sadness (r=0.78, 95% CI: 0.74, 0.82) and nausea and vomiting (r=0.67 95% CI: 0.58, 0.74). Lowest correlations were found between vomiting and difficulty remembering (r=0.087, 95% CI:
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-0.007, 0.18) and between poor appetite and numbness (0.07, 95% CI: -0.02, 0.16).
The number of factors was identified using eigenvalues together with the scree plot and parallel analysis. The scree plot shows the factors against the respective eigenvalues (Fig. 1).
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Parallel analysis “involves extracting eigenvalues of random data sets that parallel the actual data set with regard to the number of cases and variables. Factors are retained as long as the ith
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eigenvalue from the actual data is greater than the ith eigenvalue of the random data set” [22]. Results of parallel analysis, eigenvalues and the scree plot resulted in a possible three-factor solution. Principal axis factor analysis with varimax rotation was carried out for the 13 MDASIG symptom items. The eigenvalues of the three factors were 4.26, 1.41, and 1.20, explaining
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52.9 % of the variance (32.8%, 10.9%, and 9.2%, respectively). Factor 1 included affective symptoms with distress, sadness and sleep disturbance. Factor 2 included general symptoms with fatigue, drowsiness, shortness of breath, dry mouth, difficulty remembering and numbness.
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Factor 3 included gastrointestinal symptoms with nausea, vomiting, and lack of appetite. Pain loaded with 0.4 on the first factor, 0.31 on the second and 0.28 on the third factor.
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In analyzing the factor loadings, it must be noted that only distress and sadness and nausea and vomiting had factor loadings >0.8. Factor loadings are shown in Table 4. Reliability analysis for the suggested factor solution showed a Cronbach’s alpha coefficient for the first factor of 0.73 (95% CI: 0.69, 0.76), for the second factor of 0.73 (95% CI: 0.68, 0.75) and for the third factor of 0.69 (95% CI: 0.65, 0.73). The first factor, however, showed an increase of Cronbach’s alpha to 0.88 if disturbed sleep was deleted and only distress and sadness were
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tested. For the third factor, Cronbach’s alpha increased to 0.78 if poor appetite was deleted. Taking these results into account, we decided on a one-factor solution (general symptoms) with an affective and a gastrointestinal subscale.
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In addition, we performed a hierarchical cluster analysis to explore the symptom patterns. Results are presented in the dendrogram (Fig. 2). The cluster analysis again reveals high
interdependencies between single symptoms, leading to sparsely selective clusters and low intra-
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cluster distances [23] In accordance with the factor analysis, the affective and the gastrointestinal
consistent with the factor analysis.
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symptom domains are moderately prominent. Thus the results of the cluster analysis are partly
Known Group Validity. Known-group validity (sensitivity) was examined by comparing the MDASI-G total scores between patients with low functional status (ECOG PS score ≥ 2) and patients with high functional status (ECOG PS score ≤ 1). As expected, the total MDASI-G
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scores for symptom severity, symptom interference and symptom burden were significantly higher for patients with a low functional status (Table 5). Convergent and Divergent Analysis. To examine convergent validity, we calculated the
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correlations between symptom burden (mean 5.2, SD 3.5), distress (mean 5.1 SD 2.7) and global health-related quality of life (mean 49.4, SD 22.8). Pearson’s correlation coefficient (r) between
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symptom burden and global health-related quality of life was r=0.66 (95% CI: -0.70, -0.62) and between symptom burden and distress r=0.60 (95% CI: -0.56, -0.65). Both were significant twosided correlations. Discussion
The study demonstrates that the MDASI-G is a valid and reliable tool for assessing symptom intensity and interference in German cancer patients, consistent with the
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psychometrically validated versions in other languages. The MDASI-G is applicable for patients with different diagnoses and in different treatment settings. The very small number of “missings” suggests a high degree of compliance and good feasibility for everyday practice. Analysis
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showed good internal consistencies for the MDASI set of symptom items and for the set of interference items. The calculated values for Cronbach’s alpha, with 0.82 for the MDASI set of symptom items and 0.84 for the set of interference items, are comparable to other validation
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studies [1, 8-15]. For example, Cronbach’s alpha for the symptom items was reported by Njemi et al. as 0.78 [9], by Ivanova et al. as 0.80 [11] and by Yun et al. as 0.91 [10]. Construct validity
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was assessed by factor analysis. After careful consideration, we decided on a one-factor solution with gastrointestinal and affective subscales. This result is consistent with other validation studies identifying underlying constructs of a gastrointestinal factor [1, 8, 13, 15], an emotional and affective factor, and a general severity component [8, 11, 14]. As in other validation studies
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[1, 8, 11, 13, 14], the known group validity was satisfactory, showing significant differences in symptom burden for patients with “good” and “poor” ECOG PS. In order to limit the burden for patients, we did not apply a detailed reference
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questionnaire to establish concurrent validity but carried out a convergent and divergent analysis with global scores for distress and global health-related quality of life. It would have been
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interesting, however, to compare results of a questionnaire not using a 0-10 scale, e.g., the EORTC QLQ-C30 with the MDASI, as was done in other studies [8]. The descriptive results show to what extent patients are still suffering from symptom burden despite supportive therapy options. Although, corresponding to other studies, the observed low rates of vomiting indicate the success of anti-emetic treatment. Comparable to other studies [1, 8, 11, 15], fatigue was among the most prevalent and most severe symptoms, a
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finding that might motivate clinicians to perform screening and offer guideline based treatment. In addition, distress, sadness and sleep disturbance were reported frequently with moderate and severe intensity. If assessed on a regular basis, these symptoms could be taken care of early by
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psycho-oncology counseling. The result that 20.4% of the patients reported moderate pain should likewise trigger efforts to optimize symptom management. Furthermore, the assessment of symptoms in connection with functional impairments is of importance to anticipate possible
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supportive needs after discharge and the planning of after-care.
In summary these finding emphasize the importance of integrating PRO measures in
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everyday clinical practice. However, “assessment is not enough” to optimize supportive therapy [18]. It is of great importance that relevant scores of symptoms, e.g., mild and severe are followed by special diagnosis and treatment if necessary. Pathways of diagnosis and treatment have to be established and implemented. Health care professionals have to be trained in
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interpreting results and acting accordingly. Our findings of symptom severity and functional impairments in spite of existing supportive options might be interpreted against the background that this process in Germany is still evolving.
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The study had several limitations. The cross-sectional design did not allow for examining sensitivity to change. Test-retest reliability also was not addressed. Differing recruitment rates in
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the participating centers could not be explained because information about reasons for refusal was not available. For our analysis of convergence and divergence, we only measured the two global questions of the EORTC QLQ-C30 and distress. Presuming that symptom burden and global health-related quality of life and distress depict similar underlying constructs, this design was chosen in order to limit the number of questions for the patients. However, it would have been desirable to examine full convergence and divergence with respect to single symptoms of
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different instruments. The main strengths of the study were the rather large sample size comprising a comprehensive sample of cancer patients and the multicenter design. Future research using longitudinal designs could examine sensitivity to change, provide
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further information about symptom burden of cancer patients over time in different settings and stages and should include studies to verify levels and cut-off scores for symptoms and functional impairment.
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In conclusion, by measuring not only prevalence but symptom intensity and interference, the MDASI-G can provide a feasible method for screening and monitoring symptom burden in
assessment of PROs into clinical practice. Disclosures and Acknowledgments
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German-speaking countries, thus further facilitating international efforts to implement routine
This work was supported in part by ProKID [German Cancer Information Service]. The
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authors Schmidt, Bauer, Landenberger and Jahn declare no conflicts of interest. The authors thank the patients for participating in the study and cooperating so generously; the nursing departments of the five participating University hospitals who carried out
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the study; and Professor Tito Mendoza, Dipl. Psych. Dirk Rennert and Dr. rer. Nat. Christine Lautenschläger for fruitful discussion.
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23.
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Asked
Rcruited
n
n (%) 320
150 (47.9)
2
156
150 (96.1)
3
196
158 (80.6)
4
143
97 (67.8)
5
165
142 (86.1)
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1
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Center
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Table 1. Recruitment Rates
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Characteristic
n
%
Missing
60.6 a
12.9
109
Female
349
(50.1)
Marital status
693
Married, living with partner
469
(67.3)
Living alone
223
(32.0)
Education level
663
Primary school
9
Age (yrs), mean (SD) Gender
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34
(1.3)
254
Middle school
252
High school
148
ECOG PS
681
0 (fully active)
88
(12.6)
267
(38.3)
171
(24.5)
155
(22.2)
2 (ambulatory, capable of self-care)
Disease Type
(36.4) (36.2)
(21.2)
16
670
27
194
(27.8)
97
(13.9)
Genitourinary
65
(9.3)
Pulmonal
62
(8.9)
Gynecological
58
(8.3)
Head & Neck
52
(7.5)
Brain
6
(0.9)
Breast
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Gastrointestinal
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3 (capable of only limited self-care)
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Compulsory (9) yrs
1 (restricted but ambulatory)
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4
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Table 2. Participants’ Demographic and Clinical Characteristics (n =697)
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Other
136
(19.5)
Model of Care
693
In-patient
430
(61.7)
Out-patient and day clinic
263
(37.7)
Operation
407
(58.4)
Chemotherapy
511
(73.3)
Radiotherapy
195
(28.0)
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Type of treatment b
ECOG PS = Eastern Cooperative Oncology Group Performance Status. Mean age had to be computed for n=588 participants, because one center documented age groups (n=109). However no statistical difference between age groups at the recruiting centers was found, P=0.7. b Patients may have received one or more treatments.
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Table 3. Descriptive Results of MDASI-G Referring to the Last 24 Hours MDASI-G Last 24 n
Hours
Mean (SD)
Milda (%)
Moderate b (%)
-
-
Severe c (%)
Cronbach’s α
2.2 (1.5) 13 Symptom Severity Min. 0, items Max. 6.7
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(n=697)
d
-
0.82
10.2
0.81
679
2.5 (2.7)
29.8
20.4
Fatigue
679
3.3 (2.7)
33.7
28.7
14.3
0.79
Nausea
671
1.2 (2.3)
18.9
8.6
5.3
0.81
Disturbed Sleep
681
2.9 (3.0)
Distress
676
3.1 (3.0)
Shortness of breath
677
2.0 (2.6)
Difficulty remembering
677
1.2 (1.9)
Poor Appetite
681
2.2 (2.9)
Drowsiness
681
Dry mouth
680
Sadness
668
Vomiting
683
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14.5
0.81
26.1
24.5
16.1
0.81
26.5
14.9
9.2
0.82
26.7
8.5
3.0
0.82
22.8
13.8
12.3
0.80
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28.8
1.7 (2.3)
29.0
14.9
5.5
0.80
2.7 (2.9)
28.3
20.9
13.2
0.81
2.7 (2.9)
26.8
20.8
12.5
0.80
0.6 (1.6)
10.0
3.0
2.7
0.81
2.2 (2.7)
26.1
16.1
10.5
0.82
-
-
-
0.84
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Numbness or tingling
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Pain
3.0 (2.3)
6 Symptom Interference items
Min. 0,
d
Max. 10
General activity
659
3.8 (3.3)
29.3
21.1
22.4
0.82
Mood
670
2.9 (2.7)
33.6
24.7
11.2
0.83
Work
634
4.0 (3.6)
22.5
19.7
25.1
0.82
Relations with others
668
1.5 (2.3)
24.8
10.6
5.5
0.86
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Walking
671
3.3 (3.3)
24.1
18.5
21.5
0.83
Enjoyment of life
675
2.5 (2.8)
28.0
19.1
11.5
0.84
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Cronbach’s alpha coefficient for subscale. All other coefficients: Cronbach’s alpha if symptom is deleted.
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d
≥1-3, b ≥4-7, c >7-10, respectively, on a 0-10 rating scale.
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a
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Table 4. Factor Loadings for Symptom Intensity Items Symptom Item
Factor Loadings Factor 2
Factor 3
Distress
0.90
0.08
0.08
Sadness
0.90
0.05
0.15
Disturbed sleep
0.50
0.31
0.11
Pain
0.40
0.31
0.28
Shortness of breath
0.02
0.64
0.15
Fatigue
0.33
0.59
0.35
Drowsiness
0.21
0.59
0.29
Difficulty remembering
0.20
0.59
-0.03
Numbness
0.01
0.57
0.01
Dry mouth
0.18
0.47
0.33
Vomiting
0.05
0.02
0.86
Nausea
0.12
0.13
0.86
Poor appetite
0.22
0.30
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Factor 1
0.59
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Method: Principal axis factor analysis with varimax rotation. AU: PLS PROVIDE A LEGEND FOR BOLDED NUMBERS.
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Table 5. Known Group Validity ECOG PS
ECOG PS
0-1
2-4
n
N
Symptom severity
282
Symptom interference Symptom burden
ECOG 2-4
Mean Difference
Mean (SD)
Mean (SD)
(95% CI)
307
20.9 (16.7)
34.7 (18.6)
270
297
10.5 (10.0)
26.1 (12.7)
270
297
31.6 (24.9)
61.2 (28.5)
P-Value
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ECOG 0-1
-13.8 (-16.7;-10.9)
S0885-3924(14)00255-3
DOI:
10.1016/j.jpainsymman.2014.04.007
Reference:
JPS 8673
To appear in:
Journal of Pain and Symptom Management
Received Date: 6 August 2013 Revised Date:
11 April 2014
Accepted Date: 29 April 2014
Please cite this article as: Schmidt H, Cleeland CS, Bauer A, Landenberger M, Jahn P, Symptom Burden of Cancer Patients: Validation of the German M. D. Anderson Symptom Inventory. A CrossSectional Multicenter Study, Journal of Pain and Symptom Management (2014), doi: 10.1016/ j.jpainsymman.2014.04.007. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Brief Methodological Report
13-00438R1
Symptom Burden of Cancer Patients: Validation of the German M. D. Anderson Symptom
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Inventory. A Cross-Sectional Multicenter Study
Heike Schmidt, MD, Charles S. Cleeland, PhD, Alexander Bauer, PhD, Margarete
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Landenberger, PhD, and Patrick Jahn, RN, PhD
Institute for Health and Nursing Science (H.S., A.B., M.L., P.J.), Medical Faculty, Martin Luther
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University Halle-Wittenberg, and University Hospital Halle (Saale) (P.J.), Halle, Germany; and Department of Symptom Research (C.S.), The University of Texas M. D. Anderson Cancer Center, Houston, Texas, USA
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Address correspondence to: Heike Schmidt, MD
Medical Faculty, Institute for Health and Nursing Science
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Martin-Luther-University Halle-Wittenberg, Magdeburger Strasse 8
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06097 Halle, Germany
E-mail: [email protected] AU: PLS CHECK ALL AUTHOR DEGREES
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Abstract Context. Cancer patients frequently suffer from various symptoms often impairing functional status and quality of life. To enable timely supportive care, these symptoms must be
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assessed adequately with reliable tools.
Objectives. This study aimed to validate the German version of the M. D. Anderson Symptom Inventory.
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Methods. This was a multicenter, cross-sectional, observational study. At five German university hospitals, 697 cancer patients aged from 18 to 80 years undergoing active anti-cancer
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treatment were recruited to participate in the study. For the validation, reliability (Cronbach’s alpha), construct validity (factor analysis), known group validity (ECOG PS) and convergent divergent analyses were calculated.
Results. Of 980 patients who were eligible, 697 patients were included and agreed to
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participate in the study (71%). Reliability analysis showed good internal consistencies for the MDASI set of symptom items (Cronbach’s alpha coefficient = 0.82, 95% CI: 0.78, 0.84) and for the set of interference items (Cronbach’s alpha coefficient =0.857, 95% CI: 0.484, 0.87). Factor
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analysis resulted in a one-factor solution (general symptoms) (eigenvalue 4.26) with a psychological (distress and sadness) and a gastrointestinal subscale (nausea and vomiting).
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Convergent and divergent analysis showed significant correlations between symptom burden and distress and global health-related quality of life (subscale of the EORTC QLQ-C30 v. 3.0.). Conclusion. The MDASI-G is a valid tool for measuring patient reported symptom severity and symptom interference in German cancer patients. It is easily applicable and can be used by German clinicians and researchers for screening and monitoring purposes and the comparison of international data. ClinicalTrials.gov Identifier: NCT 01317355
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Key Words Cancer, symptom burden, validation, M. D. Anderson Symptom Inventory Running title: Validation of the MDASI-G
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Accepted for publication: April 29, 2014.
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Introduction Cancer patients often suffer from various disease- or treatment-related symptoms that may impair their functional status and result in high symptom burden. Unrelieved symptoms can
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limit therapy options and reduce quality of life [1]. In clinical practice, symptoms might persist unrecognized and undertreated because, when not asked, patients might not report their
symptoms exhaustively. Furthermore considerable numbers of clinicians underestimate symptom
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intensity [2, 3]. Therefore, in order to enable tailored supportive care measures, all relevant symptoms have to be assessed correctly and frequently including the patients’ perceptions.
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Patient-reported outcomes (PRO) are more and more accepted as significant measures of symptom intensity and interference as well as of health-related quality of life [1, 4-6]. However, comprehensive standardized assessments are still not widely used in daily clinical practice despite the many available and valid questionnaires. To facilitate implementation of PRO
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measures in everyday practice, it is important to provide valid but also feasible questionnaires that assess relevant symptoms [7].
The M. D. Anderson Symptom Inventory (MDASI) is a comparatively short self-
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administered questionnaire that was developed and validated to measure symptom intensity and interference in cancer patients [1]. It comprises 19 numeric rating scales (NRSs) regarding
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presence and intensity of common symptoms and functional restrictions. The MDASI assesses the severity of 13 symptoms at their worst in the last 24 hours on a 0–10 NRS, with 0 being “not present” and 10 being “as bad as you can imagine [1]. The symptom scales represent two underlying structures: a general symptom severity factor (pain, fatigue, disturbed sleep, distress (emotional), shortness of breath, drowsiness, dry mouth, sadness, difficulty remembering, and numbness or tingling) and a gastrointestinal factor (nausea and vomiting); lack of appetite loads
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on both factors [1]. A component score of symptom severity can be calculated by taking the average of the 13 items together [19]. Symptom interference with daily activities is measured by six functional scales regarding general activity, mood, work, relations with others, walking, and
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enjoyment of life. Interference is also rated on a 0–10 NRS, 0 being “did not interfere” and 10 being “interfered completely.” The mean of the interference items can be used to represent overall symptom distress. Symptom burden is defined as the sum of symptom severity and
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symptom interference [19].
Because scores of single items can be directly understood and implied in daily care
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without further computing, the MDASI can be used easily to screen or to monitor symptoms throughout the course of the treatment. It has been translated and validated in many languages including French, Taiwanese and Russian [8-15].
The main objective of this study was to gather representative information about symptom
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severity, symptom interference and symptom burden within a large heterogeneous population of cancer patients undergoing active anti-cancer treatment in different settings. In order to test and provide a relatively short disease-specific instrument with a short recall period feasible for
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screening and monitoring for future use in clinical routine, we decided to use the German version of the MDASI (MDASI-G), which already has been linguistically validated, and to perform a
Methods
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psychometric validation of this tool.
Study Design
The study was designed as a multicenter, cross-sectional, observational study to investigate symptom severity and symptom interference in a heterogeneous population of cancer patients in different settings. The validation study was carried out alongside the large descriptive
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study. Recruitment took place at the oncology departments of five German university hospitals and aimed to fulfill convenience samples of n=150 inpatients and outpatients per center. Participants
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Inclusion Criteria. Patients between 18 and 80 years of age, diagnosed with cancer and undergoing active anti-cancer treatment with an Eastern Cooperative Oncology Group
Performance Status (ECOG PS) of ≤3 who gave written informed consent were eligible to
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participate in the study.
Exclusion Criterion. Patients lacking sufficient knowledge of the German language were
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not eligible. Data Sources
To perform the psychometric validation, we used the linguistically validated MDASI-G provided by the M. D. Anderson Cancer Center. In addition, patients filled out the Distress
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Thermometer (DT), which is a short screening tool for measuring self-reported distress on a 0-10 NRS [16], and the two general questions of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-C30 (EORTC QLQ-C30), v. 3.0, regarding
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global health-related quality of life [17]. Demographic and disease-related data (age, gender,
collected.
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marital status, education level, disease type, model of care and type of treatment) also were
Ethical Considerations
As study data were not available for the physicians treating the participants, there was no direct advantage, e.g. application of supportive measures, for the participants. To reduce the burden on the patients, we limited the number of items to be answered and did not use the problem check list of the DT or another comparable reference questionnaire assessing symptoms
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and functional impairments. Patients who were not willing to participate also did not give permission to save any data. Therefore, reasons for non-participation could not be elicited. The study was approved by the local ethics committees of the participating university hospitals.
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Statistical Analysis
Scoring of the symptom severity and symptom interference scales including the handling of missing values was carried out as described in the MDASI User Guide [19]. Descriptive
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statistics were used to give an account of symptom prevalence, severity and interference. In accordance with the methodology used in the original English language validation study and
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studies validating the MDASI for foreign languages, our validation analysis plan included examination of reliability, known-group validity and analysis of convergence and divergence. To establish reliability, we examined the internal consistency (Cronbach’s alpha coefficient). To establish convergent validity, we performed a convergent and divergent analysis by testing the
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correlation of symptom burden (sum of the means of symptom severity and symptom interference) with distress (DT) and global health-related quality of life (EORTC QLQ-C30 global scale). To examine the underlying constructs that the MDASI-G is supposed to measure,
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we performed an exploratory factor analysis (EFA) on our validation sample. Because other language versions of the MDASI showed various factor solutions [1, 8, 11, 12, 14, 15], we chose
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EFA over confirmatory factor analysis (CFA) to better understand the constructs being assessed by the MDASI-G. All analyses were carried out using SPSS v. 18 (SPSS Inc. Chicago, IL). Results
Participants
Of the 980 patients who were eligible, 697 patients were included and agreed to participate in the study (71%). Recruitment sites were internal medicine (n=268, 38.5%),
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gynecology (n=146, 20.9%), surgery (n=104, 14.9%) radiotherapy (n=93, 13.3%), urology (n=58, 8.3%) head and neck (n=19, 2.7%) and dermatology (n=7, 1.0%) wards. Recruitment rates are shown in Table 1; demographic and disease-related data are shown in Table 2. As non-
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participants did not give permission to collect any data, the reasons for non-participation could not be examined. Descriptive Analyses of the MDASI-G
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Descriptive analyses were performed following the instructions given in the MDASI user guide [19]. Eleven patients did not complete the required seven items of symptom severity and
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two patients did not complete the required four items of symptom interference. Following the National Comprehensive Cancer Network guidelines for the assessment of pain [20] and the original validation study [1], we defined symptom severity as mild if it was rated between 1 and 3, moderate if it was rated between 4 and 6 and severe if it was rated equal
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or greater than 7 on the 0-10 NRS. Descriptive results for means, symptom prevalence and severity are presented in Table 3. Statistical Analyses
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Reliability. We examined internal consistency by calculating the Cronbach’s alpha coefficient. Following the rule of thumb by George and Mallery, alpha values >0.9 are rated
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excellent, > 0.8 good, >0.7 acceptable and values < 0.6 doubtful [21]. Analysis showed good internal consistencies for the MDASI set of symptom items (Cronbach’s alpha coefficient = 0.82, 95% CI: 0.80, 0.84) and for the set of interference items (Cronbach’s alpha coefficient =0.84, 95% CI: 0.82, 0.86) (Table 3). Construct Validity. Construct validity was assessed by factor analysis regarding the symptom scales. The data were suitable for factor analysis (Kaiser-Mayer-Olkin criterion: 0.80).
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The correlation matrix with Z-standardized values showed highest correlations between distress and sadness (r=0.78, 95% CI: 0.74, 0.82) and nausea and vomiting (r=0.67 95% CI: 0.58, 0.74). Lowest correlations were found between vomiting and difficulty remembering (r=0.087, 95% CI:
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-0.007, 0.18) and between poor appetite and numbness (0.07, 95% CI: -0.02, 0.16).
The number of factors was identified using eigenvalues together with the scree plot and parallel analysis. The scree plot shows the factors against the respective eigenvalues (Fig. 1).
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Parallel analysis “involves extracting eigenvalues of random data sets that parallel the actual data set with regard to the number of cases and variables. Factors are retained as long as the ith
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eigenvalue from the actual data is greater than the ith eigenvalue of the random data set” [22]. Results of parallel analysis, eigenvalues and the scree plot resulted in a possible three-factor solution. Principal axis factor analysis with varimax rotation was carried out for the 13 MDASIG symptom items. The eigenvalues of the three factors were 4.26, 1.41, and 1.20, explaining
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52.9 % of the variance (32.8%, 10.9%, and 9.2%, respectively). Factor 1 included affective symptoms with distress, sadness and sleep disturbance. Factor 2 included general symptoms with fatigue, drowsiness, shortness of breath, dry mouth, difficulty remembering and numbness.
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Factor 3 included gastrointestinal symptoms with nausea, vomiting, and lack of appetite. Pain loaded with 0.4 on the first factor, 0.31 on the second and 0.28 on the third factor.
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In analyzing the factor loadings, it must be noted that only distress and sadness and nausea and vomiting had factor loadings >0.8. Factor loadings are shown in Table 4. Reliability analysis for the suggested factor solution showed a Cronbach’s alpha coefficient for the first factor of 0.73 (95% CI: 0.69, 0.76), for the second factor of 0.73 (95% CI: 0.68, 0.75) and for the third factor of 0.69 (95% CI: 0.65, 0.73). The first factor, however, showed an increase of Cronbach’s alpha to 0.88 if disturbed sleep was deleted and only distress and sadness were
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tested. For the third factor, Cronbach’s alpha increased to 0.78 if poor appetite was deleted. Taking these results into account, we decided on a one-factor solution (general symptoms) with an affective and a gastrointestinal subscale.
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In addition, we performed a hierarchical cluster analysis to explore the symptom patterns. Results are presented in the dendrogram (Fig. 2). The cluster analysis again reveals high
interdependencies between single symptoms, leading to sparsely selective clusters and low intra-
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cluster distances [23] In accordance with the factor analysis, the affective and the gastrointestinal
consistent with the factor analysis.
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symptom domains are moderately prominent. Thus the results of the cluster analysis are partly
Known Group Validity. Known-group validity (sensitivity) was examined by comparing the MDASI-G total scores between patients with low functional status (ECOG PS score ≥ 2) and patients with high functional status (ECOG PS score ≤ 1). As expected, the total MDASI-G
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scores for symptom severity, symptom interference and symptom burden were significantly higher for patients with a low functional status (Table 5). Convergent and Divergent Analysis. To examine convergent validity, we calculated the
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correlations between symptom burden (mean 5.2, SD 3.5), distress (mean 5.1 SD 2.7) and global health-related quality of life (mean 49.4, SD 22.8). Pearson’s correlation coefficient (r) between
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symptom burden and global health-related quality of life was r=0.66 (95% CI: -0.70, -0.62) and between symptom burden and distress r=0.60 (95% CI: -0.56, -0.65). Both were significant twosided correlations. Discussion
The study demonstrates that the MDASI-G is a valid and reliable tool for assessing symptom intensity and interference in German cancer patients, consistent with the
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psychometrically validated versions in other languages. The MDASI-G is applicable for patients with different diagnoses and in different treatment settings. The very small number of “missings” suggests a high degree of compliance and good feasibility for everyday practice. Analysis
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showed good internal consistencies for the MDASI set of symptom items and for the set of interference items. The calculated values for Cronbach’s alpha, with 0.82 for the MDASI set of symptom items and 0.84 for the set of interference items, are comparable to other validation
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studies [1, 8-15]. For example, Cronbach’s alpha for the symptom items was reported by Njemi et al. as 0.78 [9], by Ivanova et al. as 0.80 [11] and by Yun et al. as 0.91 [10]. Construct validity
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was assessed by factor analysis. After careful consideration, we decided on a one-factor solution with gastrointestinal and affective subscales. This result is consistent with other validation studies identifying underlying constructs of a gastrointestinal factor [1, 8, 13, 15], an emotional and affective factor, and a general severity component [8, 11, 14]. As in other validation studies
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[1, 8, 11, 13, 14], the known group validity was satisfactory, showing significant differences in symptom burden for patients with “good” and “poor” ECOG PS. In order to limit the burden for patients, we did not apply a detailed reference
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questionnaire to establish concurrent validity but carried out a convergent and divergent analysis with global scores for distress and global health-related quality of life. It would have been
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interesting, however, to compare results of a questionnaire not using a 0-10 scale, e.g., the EORTC QLQ-C30 with the MDASI, as was done in other studies [8]. The descriptive results show to what extent patients are still suffering from symptom burden despite supportive therapy options. Although, corresponding to other studies, the observed low rates of vomiting indicate the success of anti-emetic treatment. Comparable to other studies [1, 8, 11, 15], fatigue was among the most prevalent and most severe symptoms, a
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finding that might motivate clinicians to perform screening and offer guideline based treatment. In addition, distress, sadness and sleep disturbance were reported frequently with moderate and severe intensity. If assessed on a regular basis, these symptoms could be taken care of early by
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psycho-oncology counseling. The result that 20.4% of the patients reported moderate pain should likewise trigger efforts to optimize symptom management. Furthermore, the assessment of symptoms in connection with functional impairments is of importance to anticipate possible
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supportive needs after discharge and the planning of after-care.
In summary these finding emphasize the importance of integrating PRO measures in
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everyday clinical practice. However, “assessment is not enough” to optimize supportive therapy [18]. It is of great importance that relevant scores of symptoms, e.g., mild and severe are followed by special diagnosis and treatment if necessary. Pathways of diagnosis and treatment have to be established and implemented. Health care professionals have to be trained in
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interpreting results and acting accordingly. Our findings of symptom severity and functional impairments in spite of existing supportive options might be interpreted against the background that this process in Germany is still evolving.
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The study had several limitations. The cross-sectional design did not allow for examining sensitivity to change. Test-retest reliability also was not addressed. Differing recruitment rates in
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the participating centers could not be explained because information about reasons for refusal was not available. For our analysis of convergence and divergence, we only measured the two global questions of the EORTC QLQ-C30 and distress. Presuming that symptom burden and global health-related quality of life and distress depict similar underlying constructs, this design was chosen in order to limit the number of questions for the patients. However, it would have been desirable to examine full convergence and divergence with respect to single symptoms of
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different instruments. The main strengths of the study were the rather large sample size comprising a comprehensive sample of cancer patients and the multicenter design. Future research using longitudinal designs could examine sensitivity to change, provide
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further information about symptom burden of cancer patients over time in different settings and stages and should include studies to verify levels and cut-off scores for symptoms and functional impairment.
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In conclusion, by measuring not only prevalence but symptom intensity and interference, the MDASI-G can provide a feasible method for screening and monitoring symptom burden in
assessment of PROs into clinical practice. Disclosures and Acknowledgments
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German-speaking countries, thus further facilitating international efforts to implement routine
This work was supported in part by ProKID [German Cancer Information Service]. The
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authors Schmidt, Bauer, Landenberger and Jahn declare no conflicts of interest. The authors thank the patients for participating in the study and cooperating so generously; the nursing departments of the five participating University hospitals who carried out
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the study; and Professor Tito Mendoza, Dipl. Psych. Dirk Rennert and Dr. rer. Nat. Christine Lautenschläger for fruitful discussion.
1.
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23.
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Asked
Rcruited
n
n (%) 320
150 (47.9)
2
156
150 (96.1)
3
196
158 (80.6)
4
143
97 (67.8)
5
165
142 (86.1)
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1
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Center
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Table 1. Recruitment Rates
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Characteristic
n
%
Missing
60.6 a
12.9
109
Female
349
(50.1)
Marital status
693
Married, living with partner
469
(67.3)
Living alone
223
(32.0)
Education level
663
Primary school
9
Age (yrs), mean (SD) Gender
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34
(1.3)
254
Middle school
252
High school
148
ECOG PS
681
0 (fully active)
88
(12.6)
267
(38.3)
171
(24.5)
155
(22.2)
2 (ambulatory, capable of self-care)
Disease Type
(36.4) (36.2)
(21.2)
16
670
27
194
(27.8)
97
(13.9)
Genitourinary
65
(9.3)
Pulmonal
62
(8.9)
Gynecological
58
(8.3)
Head & Neck
52
(7.5)
Brain
6
(0.9)
Breast
AC C
Gastrointestinal
EP
3 (capable of only limited self-care)
TE D
Compulsory (9) yrs
1 (restricted but ambulatory)
SC
4
RI PT
Table 2. Participants’ Demographic and Clinical Characteristics (n =697)
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Other
136
(19.5)
Model of Care
693
In-patient
430
(61.7)
Out-patient and day clinic
263
(37.7)
Operation
407
(58.4)
Chemotherapy
511
(73.3)
Radiotherapy
195
(28.0)
RI PT
4
SC
Type of treatment b
ECOG PS = Eastern Cooperative Oncology Group Performance Status. Mean age had to be computed for n=588 participants, because one center documented age groups (n=109). However no statistical difference between age groups at the recruiting centers was found, P=0.7. b Patients may have received one or more treatments.
AC C
EP
TE D
M AN U
a
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Table 3. Descriptive Results of MDASI-G Referring to the Last 24 Hours MDASI-G Last 24 n
Hours
Mean (SD)
Milda (%)
Moderate b (%)
-
-
Severe c (%)
Cronbach’s α
2.2 (1.5) 13 Symptom Severity Min. 0, items Max. 6.7
RI PT
(n=697)
d
-
0.82
10.2
0.81
679
2.5 (2.7)
29.8
20.4
Fatigue
679
3.3 (2.7)
33.7
28.7
14.3
0.79
Nausea
671
1.2 (2.3)
18.9
8.6
5.3
0.81
Disturbed Sleep
681
2.9 (3.0)
Distress
676
3.1 (3.0)
Shortness of breath
677
2.0 (2.6)
Difficulty remembering
677
1.2 (1.9)
Poor Appetite
681
2.2 (2.9)
Drowsiness
681
Dry mouth
680
Sadness
668
Vomiting
683
M AN U 21.1
14.5
0.81
26.1
24.5
16.1
0.81
26.5
14.9
9.2
0.82
26.7
8.5
3.0
0.82
22.8
13.8
12.3
0.80
TE D
28.8
1.7 (2.3)
29.0
14.9
5.5
0.80
2.7 (2.9)
28.3
20.9
13.2
0.81
2.7 (2.9)
26.8
20.8
12.5
0.80
0.6 (1.6)
10.0
3.0
2.7
0.81
2.2 (2.7)
26.1
16.1
10.5
0.82
-
-
-
0.84
EP 681
AC C
Numbness or tingling
SC
Pain
3.0 (2.3)
6 Symptom Interference items
Min. 0,
d
Max. 10
General activity
659
3.8 (3.3)
29.3
21.1
22.4
0.82
Mood
670
2.9 (2.7)
33.6
24.7
11.2
0.83
Work
634
4.0 (3.6)
22.5
19.7
25.1
0.82
Relations with others
668
1.5 (2.3)
24.8
10.6
5.5
0.86
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Walking
671
3.3 (3.3)
24.1
18.5
21.5
0.83
Enjoyment of life
675
2.5 (2.8)
28.0
19.1
11.5
0.84
TE D
M AN U
SC
RI PT
Cronbach’s alpha coefficient for subscale. All other coefficients: Cronbach’s alpha if symptom is deleted.
EP
d
≥1-3, b ≥4-7, c >7-10, respectively, on a 0-10 rating scale.
AC C
a
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Table 4. Factor Loadings for Symptom Intensity Items Symptom Item
Factor Loadings Factor 2
Factor 3
Distress
0.90
0.08
0.08
Sadness
0.90
0.05
0.15
Disturbed sleep
0.50
0.31
0.11
Pain
0.40
0.31
0.28
Shortness of breath
0.02
0.64
0.15
Fatigue
0.33
0.59
0.35
Drowsiness
0.21
0.59
0.29
Difficulty remembering
0.20
0.59
-0.03
Numbness
0.01
0.57
0.01
Dry mouth
0.18
0.47
0.33
Vomiting
0.05
0.02
0.86
Nausea
0.12
0.13
0.86
Poor appetite
0.22
0.30
TE D
M AN U
SC
RI PT
Factor 1
0.59
AC C
EP
Method: Principal axis factor analysis with varimax rotation. AU: PLS PROVIDE A LEGEND FOR BOLDED NUMBERS.
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Table 5. Known Group Validity ECOG PS
ECOG PS
0-1
2-4
n
N
Symptom severity
282
Symptom interference Symptom burden
ECOG 2-4
Mean Difference
Mean (SD)
Mean (SD)
(95% CI)
307
20.9 (16.7)
34.7 (18.6)
270
297
10.5 (10.0)
26.1 (12.7)
270
297
31.6 (24.9)
61.2 (28.5)
P-Value
RI PT
ECOG 0-1
-13.8 (-16.7;-10.9)
