Six independent domains are defined by geriatric assessment in elderly cancer patients

Critical Reviews in Oncology/Hematology 74 (2010) 97–105

Six independent domains are defined by geriatric assessment in elderly cancer patients夽 R. Stauder a,∗ , K. Moser a , B. Holzner b , B. Sperner-Unterweger b , G. Kemmler b a

Department of Internal Medicine V (Haematology and Oncology), Innsbruck Medical University, Anichstrasse 35, 6020 Innsbruck, Austria b Department of Biological Psychiatry, Innsbruck Medical University, Austria Accepted 29 April 2009

Contents 1. 2.

3.

4.

Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Materials and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Patients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Assessment instruments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3. Statistical methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Geriatric assessment in elderly cancer patients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.1. Performance status and functional activities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.2. Activities of daily living . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.3. Quality of life . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.4. Depression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.5. Comorbidities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.6. Cognitive function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.7. Social support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Results of factor analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3. Confirmation of factor structure by correlation analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4. Relevance of performance and screening scores in detecting the different domains . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conflict of interest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Reviewers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Biographies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

98 98 98 98 99 99 99 99 99 99 100 100 100 100 100 100 100 101 103 103 103 103 104

Abstract Background: Geriatric assessment (GA) must be integrated into treatment concepts for elderly cancer patients. Aim of this study was to assess the coverage of a large battery of GA instruments by determining the number of independent domains measured. Methods: Thirteen different GA scores were applied in 78 elderly tumor patients (mean age 72.9 years). Data were analyzed by exploratory factor analysis and substantiated by non-parametric correlation analyses. Results: Factor analysis yielded a six-factor solution explaining 77.1% of the total variance. The six domains identified may be described as general functioning in everyday life, health-related quality of life, co-morbidities, social support, cognition, and nutritional status. This factor structure was reasonably well confirmed by correlation analyses. Notably, WHO Performance Status, Karnofsky Index, VES-13 and

夽 ∗

Parts of this manuscript were presented at the 9th Meeting of the International Society of Geriatric Oncology in Montreal, Canada. Corresponding author. Tel.: +43 512 504 23255. E-mail address: [email protected] (R. Stauder).

1040-8428/$ – see front matter © 2009 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.critrevonc.2009.04.010

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PPT generally revealed high correlations with functional capacities, but only low correlations with comorbidities, social support, cognitive functioning or nutritional status. Conclusions: From the six domains described a basis for efficient application of GA instruments in elderly cancer patients is worked out. The classical instruments WHO and KI as well as the screening scores VES-13 and PPT, while capturing physical functioning well, fail to cover several other important GA domains. © 2009 Elsevier Ireland Ltd. All rights reserved. Keywords: Geriatric; Assessment; Elderly; Cancer; Factor analysis; Screening

1. Introduction Due to demographic changes the number of elderly cancer patients is progressively increasing [1]. As 60% of malignancies occur in patients over the age of 65, the demand for specialized care of patients who suffer from symptoms and limitations related to both senescence and cancer is growing rapidly [2,3]. To understand and meet the needs of elderly tumor patients, geriatricians and oncologists have thus established and integrated the geriatric assessment (GA) into decision analysis and treatment concepts [4]. The GA represents a structured approach that was originally designed to use reliable scores to assess different domains like functional activities, comorbidities, emotional situation, cognition, quality of life, and social support to identify resources and needs. Moreover, it was found that different portions of the CGA, namely function and comorbidity, may help define physiologic age and predict individual life-expectancy, while function, comorbidities and social support may predict tolerance and toxicity of chemotherapy [4–6]. The GA is a stepwise process. GA tests range from simple screening tools, which can be applied by oncologists, to highly complex instruments to be used and evaluated by specialists. Overall the application of GA instruments in the elderly is time-consuming and costly. Aim of this study was to assess the coverage of a large battery of GA instruments by determining the number of independent domains measured and how these domains are related to the individual GA tools. This has to be seen as an essential prerequisite for the final goal of setting up a GA test battery for use in the clinical routine, namely for the purpose of assessing a sufficiently wide range of aspects with the smallest possible amount of time and effort. 2. Materials and methods 2.1. Patients Geriatric assessment was performed in 78 tumor patients aged 60+ (range 60–93; median 72.5 years). The cohort included 37 female and 41 male persons. The tumors involved were 64 hematological malignancies and 14 cases of solid tumors (Table 1). The study was performed in inpatients at the Department of Internal Medicine V (Haematology and Oncology) of Innsbruck Medical University, Austria, after having obtained informed consent. Patients were admitted

to the ward to start chemotherapy in 19 cases, to start immunochemo-therapy mainly R-COP or R-CHOP in six cases, antibody therapy consisting of rituximab and bevacizumab in nine cases. The other patients were admitted for supportive therapy or for diagnostic workup. This work was approved by the local ethics committee and was carried out in accordance with The Code of Ethics of the World Medical Association (Declaration of Helsinki) for experiments involving humans. 2.2. Assessment instruments Traditional scores applied were the WHO Performance Status [7] and the Karnofsky Index [8]. Functional activities were assessed by means of the scores Activities of Daily Life (ADL) (Barthel Index) [9], Instrumental Activities of Daily Living (IADL) [10] and the Timed Up and Go Test [11]. Screening instruments used were the 7-item physical performance test (PPT) [12,13] and the Vulnerable Elderly Survey 13 (VES-13) [14]. Health-related quality of life was assessed with the Functional Assessment of Cancer Therapy General Scale (FACT-G) [15,16]. Screening for depression was assessed with the Geriatric Depression Scale (GDS) [17]. Cognitive function was evaluated with the Mini Mental Status Examination (MMSE) [18]. Comorbidities were evaluated using the Cumulative Illness Rating Scale for Geriatricians (CIRS-G) [19] as well as the Charlson Comorbidity Index (CCI) [20]. Social support was evaluated with the F-SozU (Questionnaire for the assessment of social support). The Table 1 Patient characteristics. Entity

N

%

Non-Hodgkin’s lymphoma (indolent)a Non-Hodgkin’s lymphoma (aggressive)b Multiple myeloma M. Hodgkin MDS, AML, CML, PVc Solid tumord

24 16 7 1 16 14

31 21 9 1 21 18

a Was made up of 17 cases of chronic lymphocytic leukemia (CLL) and 7 cases of follicular lymphoma. b 16 cases of diffuse large B-cell lymphoma (DLBCL). c This group consisted of 5 cases of myelodysplastic syndrome (MDS), 7 cases of acute myeloid leukemia (AML), 3 cases of chronic myeloid leukemia (CML) and 1 case of polycythemia vera (PV). d Solid tumors included: lung cancer (2), breast cancer (2), colorectal cancer (2) and 1 case of gastric cancer, renal cell carcinoma, bladder cancer, pancreatic cancer, cancer of unknown primary (adenocarcinoma), hepatocellular carcinoma, pleural mesothelioma and leiomyosarcoma.

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Table 2 Geriatric assessment in elderly cancer patients. Assessment score

Karnofsky Index ADL WHO Performance Status VES-13 IADL PPT Timed Up and Gob FACT-G total score GDS-30 CIRS-Gd Charlson Comorbidity Index F-SozUe MMSE BMIf a b c d e f

Range

10–100 15–100 0–4 0–9 1–8 3–25 4–97.2 40–108 0–27 0–16 0–5 1.90–5 14–30 15.0–31.9

Mean

79.5 93.1 1.3 3.1 6.1 17.3 13.9 81.6 8.3 6.0 1.6 4.3 25.8 24.5

Median

90 100 1 2 7 18 11.2 85 7.5 5.5 1 4.3 27 24.7

Standard deviation

18.23 13.27 0.89 2.84 2.02 4.91 11.98 16.75 5.62 4.51 1.43 0.59 3.67 3.67

n

78 78 78 78 78 64 60 78 78 78 78 71 78 74

Clinically relevant categories Cut-off point

Positive (%)a

≤70 ≤90 ≥2 ≥3 ≤7 >20 ≥20b –c >9 ≥1 ≥2 <3.27 ≤24 <18.5f ≥25.0f

26 31 39 41 62 76 12 10 32 59 47 3 26 7 47

Numbers rounded to the nearest integer number. Measured in seconds. Age- and gender-dependent cut-off values (10th percentile of population-based sample [36]). The number of grade III or IV comorbidities was evaluated. Based on the definition outlined in [22], <3.27 was applied as the lower reference value (based on mean minus one standard deviation). Measured in kg/m2 .

F-SozU is a written self-reporting questionnaire measuring perceived social support and satisfaction with social support. The original version consists of 54 items; the current study used the abbreviated 22-item version [21,22]. The body mass index (BMI) is a relevant item for nutritional assessment. The BMI was calculated and classified as suggested by the World Health Organization (WHO). 2.3. Statistical methods The main part of the analysis consisted of an exploratory factor analysis with subsequent Varimax rotation. The eigenvalue criterion was used to determine the adequate number of factors [23]. All assessment instruments described above were used in this analysis, except for two scales with a substantial proportion of missing values (PPT: 18%; timed up and go, 23%). In the case of the FACT-G, subscales, namely the domains social, physical, functional and well-being, rather than the total score were entered into the factor analysis since these subscales are known to measure distinct domains of QOL [15]. Additional correlation analyses were performed to confirm the findings of the factor analysis. Non-parametric correlation coefficients (Spearman rho) were used owing to the skewed distribution of several of the scales involved. 3. Results 3.1. Geriatric assessment in elderly cancer patients 3.1.1. Performance status and functional activities A relevant proportion of patients were identified, who displayed a reduced performance status (Table 2). The

Karnofsky Index (KI) was ≤40 (unable to take care of themselves) in 4%, 50–70 (unfit for work) in 21.7%, whereas a basically normal activity ≥80 was found in 74.3% of patients. The WHO Performance Status was 0 (asymptomatic) in 20.5%, 1 in 41%, 2 in 32.1%, 3 in 5.1% and 4 (bedbound) in 1.3%. 3.1.2. Activities of daily living About one-third of the patients displayed restricted activities as defined by ADL Scale: 100-91 (independent): 70.5%; 90-61 (moderate impairment): 26.9%; 60-21 (severe impairment): 1.3%, 20-0: 1.3%. With regard to instrumental activities an IADL Scale of 8 (independent) was detected in 38.5 %, whereas 61.5% of patients revealed one or several dependencies (IADL 0–7). Using the screening score VES13, 41% of patients were identified as vulnerable (VES-13 ≥3). Similarly, moderate (PPT 20–11) and severe impairment (PPT <11) were detected in 67.1% and 9.3% of cases, respectively, whereas no impairment (PPT >20) was detected in only 23.4% of patients. However, because of imbalance and fear of falls when executing a 360◦ turn, the PPT could not be performed in 14 patients. The Timed Up and Go Test was performed in 36.7% of patients in less than 10 s, in 51.7% in 10.1–20 s and in 11.7% in >20 s. However, similarly to the PPT, the Timed Up and Go Test could not be performed in 18 patients. 3.1.3. Quality of life The patient sample displayed a mean FACT-G total score of 81.6 (range 27–108); 10.3% of the patients had a total FACT-G score below the proposed cut-off value for reduced quality of life.

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3.1.4. Depression In the depression screening GDS-30, a substantial proportion was positive: depression probable (10–19): 28.2%; depression highly probable (≥20): 3.85%, whereas 67.95% were classified as non-depressive (0–9). 3.1.5. Comorbidities When assessing comorbidities using the CIRS-G the total score revealed a median of 5.5 and the number of categories involved was median 3 (range; 0–8); grade 3 comorbidities were observed in 48.7% (1: 34.6%; 2: 12.8% and 3: 1.3%) and grade 4 comorbidities in 25.7% (1: 23.1% and 2: 2.6%). The Charlson Comorbidity Index was 0: 29.5%, 1: 23.1%; 2; 17.9%, 3; 16.7%; 4:11.5% and 5: 1.3%. 3.1.6. Cognitive function Screening of cognitive functions revealed moderately reduced cognition (MMSE ≤24) in 25.6% and an MMSE of 25–30 in 74.4% of cases. 3.1.7. Social support The majority of patients were characterized by good social support: 58% were living with their partner, 26% with family members, 3% needed outside help, another 13% lived on their own. Only two persons were living in a nursing home. Accordingly, 97.2% of the patients scored more than 3.27 points on the F-SozU, thus indicating good social support, whereas only 2.8% of cases scored >3.27. Nutritional status: Underweight as defined as a BMI < 18.5 kg/m2 was detected in 7% of the patients; a normal range of 18.5–24.99 kg/m2 was detected in 46%, overweight as defined as a BMI > 25.00 kg/m2 in 47%. However, obesity ≥30.00 kg/m2 was found in only 4%. 3.2. Results of factor analysis Factor analysis yielded a solution in which six factors explained 77.1% of the total variance. This means that the complete set of GA scales and subscales considered in this study can be summarized in six independent domains, whereas further reduction (to five domains or less) would be inappropriate. The six domains identified may be briefly described as functional status, health-related quality of life, comorbidities, social support, cognition and nutritional status. A more detailed description is given below. Results of the analysis are also shown in Table 3. - The following scores loaded highly on Domain 1: Karnofsky Index, ADL, WHO Performance Status, VES-13 and IADL. This factor assesses general functioning or performance in everyday life. PPT and the “Timed Up and Go” Test were not included in the factor analysis because they involved a high proportion of missing values. However, these two scales also had their highest loadings on factor 1. - The following scales had their highest loading on Domain 2: three subscales of the FACT-G (physical, emotional and

-

-

functional well-being) and the GDS-30. This factor covers physical, emotional and functional aspects of the patient’s self-perceived quality of life. Not surprisingly, the FACTG functional well-being subscale had a rather high sideloading on “functional” factor 1. The total score and the grade 3 comorbidities (G3) subscore of the CIRS-G both loaded highly on Domain 3, which measures the extent of comorbidities. The Charlson Comorbidity Index also showed a rather high loading on this factor. The CIRS number of categories also loaded highly on this factor, whereas the grade 4 comorbidities (G4) subscore displayed a much lower loading of only 0.29 (as the latter scale loaded low on all factors, it was excluded from the analysis). The FACT-G social well-being subscale and the F-SozU both had high loadings on Domain 4, apparently addressing social support. The MMSE loaded on a separate fifth domain, cognitive functioning. One other scale showed an appreciable sideloading on this factor, namely the IADL. This underlines the relevance of cognition in the performance of instrumental activities. A sixth independent domain was defined by BMI, which is a relevant nutritional status item. This factor showed little overlap with the other factors, as indicated by the low side-loadings of other items in this domain.

3.3. Confirmation of factor structure by correlation analysis In general, the factor structure was reasonably well confirmed by correlation analysis. Almost all correlations among (sub-)scales belonging to the same factor were at least moderately high, with Spearman correlation coefficients lying above 0.4. In the majority of cases, correlations between (sub-)scales belonging to different factors were fairly low (rSpearman < 0.4, usually considerably lower). There were a few exceptions from this rule, in particular a certain overlap between factor 1 (general level of functioning) and factor 2 (quality of life) and between factors 2 and 4 (social support). However, separate factor analyses revealed that neither factors 1 and 2 nor factors 2 and 4 can be condensed to a single factor. 3.4. Relevance of performance and screening scores in detecting the different domains To evaluate detection of the six domains by standard performance ratings widely used in oncology and by screening tests, additional correlation analyses were performed (Table 4). WHO Performance Status, KI, VES-13 and PPT generally revealed high correlations with functional capacities (domain 1); only the correlation with IADL showed lower values, maybe due to the relevance of cognition in IADL. Moderate correlations were observed between these instruments (WHO, KI, VES-13) and the functional and

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Table 3 Factor analysis reveals six distinct domains. Scale/subscale

Domain 1 (functional activities)

Domain 1 Karnofsky Index ADL WHO performance VES-13 IADL PPTa Timed Up and Goa

.883 .831 −.807 −.792 .631 .587 −.434

Domain 2 FACT-G EWB FACT-G PWB GDS-30 FACT-G FWB

−.200 .373 −.266 .480

Domain 3 CIRS-G totalb CIRS-G categoriesc CIRS-G 3d Charlson Domain 4 F-SozU FACT-G SWB

2 (health-related quality of life)

3 (comorbidities)

4 (social support)

5 (cognitive function)

6 (nutritional status)

−.286

.407 .254 −.218 .771 .759 −.655 .559

−.201 −.214

.319 −.280 .397 .929 .891 .799 .585

.218

.216

−.342 .885 .844

Domain 5 MMSE

−.355

.282 .904

Domain 6 BMI

.925

Significant loadings are marked in grey. a As the proportion of missing values was high, factor loadings were evaluated in separate correlation analyses. b CIRS-G total: score achieved in CIRS-G. c CIRS-G categories: number of categories involved. d CIRS-G 3: number of categories displaying a grade 3 severity.

physical well-being subscales of FACT-G and GDS (domain 2). The domains of comorbidity, social support, cognitive functioning and nutritional status, however, showed very low correlations with WHO, KI, VES-13 and PPT. These findings clearly demonstrate that WHO, KI, VES-13 and PPT, while capturing physical functioning rather well, do not give a complete picture of comorbidities, namely social support, cognition and nutritional status.

4. Discussion Advanced age is not only associated with a growing incidence of tumors, but also with an increase in illnesses and health problems. Therefore, therapeutic approaches in older persons with cancer need to be based upon an understanding of the heterogeneity of the health and functional status of older persons as evaluated by appropriate assessment instruments. The special aspect of this analysis is that numerous assessment instruments were applied simultaneously in one and the same patient. In this way it was possible to determine which of the scores used in the assessment cover overlapping

aspects and which of them address different domains. Using factor analysis the six domains functional status, quality of life, co-morbidities, social support, cognition and nutritional status were identified as independent dimensions covered by the GA. None of the six factors defined can be replaced by any of the other dimensions or by a combination of them. Traditionally, the dimension functional status is evaluated by oncologists by applying the Karnofsky Index [8] or the WHO (ECOG) Performance Status [7]. By contrast, evaluation by geriatricians includes the assessment of activities of daily living (ADL) or instrumental activities of daily living (IADL). These scales assess the capacities in a given patient to maintain basic activities at home like the ability to dress, eat or move and define the need for functional assistance. In addition, the IADL assesses activities essential for living independently in the community like making telephone calls, managing financial affairs or organizing transportation [6]. The relevance of the domain of functional capacities is highlighted by this study: this domain encompasses the Karnofsky Index, WHO Performance Status, ADL and the VES-13. The IADL, PPT and the “Timed Up and Go” test revealed a lower loading. The lower loading of the latter test might reflect the

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Table 4 Coverage of different domains by performance and screening scores. Test

rSpearman (*p < 0.05; **p < 0.01) WHO

Karnofsky

VES-13

PPT

−0.822**

−0.670** −0.648**

−0.648** 0.605** −0.572**

WHO Karnofsky VES-13 PPT Timed Up and Go ADL IADL

−0.822** −0.670** 0.491** 0.600** −0.556** −0.410**

FACT-G PWB FACT-G EWB FACT-G FWB GDS-30

−0.459** −0.161 −0.477** 0.331**

0.487** 0.278* 0.645** −0.435**

−0.438** −0.131 −0.498** 0.468**

0.214 0.123 0.174 0.201

−0.321** −0.167 −0.228* −0.280*

0.348** 0.187 0.113 0.291**

FACT-G SWB F-SozU

−0.119 −0.109

0.305** 0.305**

−0.127 −0.274*

MMSE BMI

−0.228* 0.181

0.152 0.161

−0.314** −0.155

CIRS-G total score CIRS-G 3 CIRS-G 4 Charlson Index

−0.648** 0.605** −0.558** 0.660** 0.380**

−0.572** 0.488** −0.714** −0.487**

−0.612** 0.491** 0.227 0.377** 0.142 0.312* −0.298* −0.199 −0.057 −0.140 −0.118 0.195 0.086 0.137 −0.023

Correlation coefficients based on Spearman rho analysis are shown. R values >0.3 are displayed in bold, whereas R values >0.5 are marked in grey.

fact that this score was originally designed to evaluate physical capabilities and specifically to predict the patient’s ability to walk alone safely [11]. The IADL revealed a side-loading on the MMSE, showing the relevance of cognitive capacities for distinct instrumental activities. If several scales have high loadings (>0.7) on the same factor, this indicates that some of these scales may not be required, as they are sufficiently covered by the other scales. Thus, it might be pertinent to discuss the possibility of replacing KI (loading of 0.876 on the first factor), WHO (0.803) and ADL (0.834) with one another. In contrast, the IADL exhibiting a lower loading on the first factor (0.648) and a fairly high side-loading on the cognition factor should not be replaced with KI, WHO or ADL, but should be evaluated separately. This supports evidence from several studies showing that the IADL substantially adds to the information obtained by means of KI or WHO [24]. Pretreatment IADL values, but not ADLs, predict survival in NSCLC [25] and an increased risk for postoperative complications [26]. The second domain comprises the physical, emotional and functional aspects of the patient’s self-perceived quality of life (assessed with the pertinent subscales of the FACT-G) as well as depression, as measured with the GDS-30. Although this dimension may appear somewhat heterogeneous in itself, correlation analyses have shown that the various aspects are sufficiently related to each other to be integrated into the same domain. The scales of this domain have in common that they measure self-perceived well-being or the lack of it, the latter frequently being accompanied by symptoms of depression [27]. About one-third of the patients in this study showed at least mild depression according to the GDS-30.

Thus, assessment of depression is an important aspect of the GA in elderly cancer patients. This is substantiated by the fact that depression symptoms are often underestimated (or depression is poorly recognized) by oncologists [28], as is the potential relevance of depression symptoms as a risk factor in cancer patients [29]. Assessment of comorbidities (cm) is essential for the overall prognosis and in decision-making in the elderly. The total score and the grade 3 (G3) subscore of the CIRS-G both loaded highly on Domain 3, which measures the extent of comorbidities. The Charlson Comorbidity Index also showed a rather high loading on this factor. Cm clearly complicate and influence diagnostic approaches and treatment concepts and are associated with a reduction in life-expectancy and treatment tolerance [6,30,31]. In agreement with earlier analyses [32] the results of this study reveal that cm scales cannot be replaced with other instruments. Thus, a routine assessment of cm should be included in elderly cancer patients to evaluate cm as an important determinant and potential confounder of patient outcome and study results. The FACT-G social well-being subscale and the F-SozU both had high loadings on Domain 4. The first (sub-)scale measures social support in general [15,33], the second assesses both the instrumental and the emotional component of social support [21,22]. The latter domain therefore covers the dimension of social support sufficiently broadly. Evaluation of social support is an essential part of geriatric assessment as social isolation results in an augmented risk of overall and tumor-associated mortality [6]. Cognitive function was clearly identified as an independent domain by factor analysis. Apart from the MMSE, the

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IADL revealed a relevant side-loading on this dimension, demonstrating the relevance of cognition in the exertion of instrumental activities. As cognitive function in a given patient impacts clinical outcome by influencing medical decisions as well as compliance and adherence to therapies [34,35], this dimension should be integrated in treatment concepts and risk stratification in the elderly. Nutritional assessment is a major issue in evaluating the health status of senior adults. Weight loss and low body mass index are associated with shortened survival in cancer patients [6]. The relevance of nutritional assessment in elderly cancer patients is underlined by its definition as an independent dimension in this analysis. Several screening tools established in geriatrics have so far been used in cancer patients. Screening tools are designed to predict who is a “fit” or a “vulnerable” oncogeriatric patient and who is in need of a comprehensive, multidisciplinary evaluation. VES-13 [14] and PPT [12] were described as general geriatric screening tools. VES-13 predicts functional decline or death in elderly individuals [14], whereas PPT provides an objective measurement of physical function [12]. However, valid data on screening in cancer patients are pending. In the present study both VES-13 and PPT were mainly assigned to the functional domain. These findings demonstrate that VES-13 and PPT, while capturing physical functioning rather well, only incompletely cover the important domains of comorbidities, social support, cognition and nutritional status. Clearly, we do not question the usefulness of these instruments for measuring physical (PPT) and functional status (VES-13) in the elderly. There is also no doubt that maintaining and restoring a person’s functional status remains a key issue in geriatrics. However, we argue that a comprehensive GA should include a broader range of issues and that the screening scales developed so far, namely PPT or VES-13, are not sufficient to cover all of these. Likewise, the WHO Performance Status and the KI failed to cover the domains of comorbidities, social support, QOL and cognition, demonstrating that traditional oncology measures like the KI or the WHO Performance Status are insufficient in older patients and should be supplemented with scores covering the above-mentioned domains. It should be noted that the important issue of evaluating screening instruments for diagnostic purposes was beyond the scope of this work. To appropriately deal with this issue, a larger sample and other methods of analysis are required. The results presented in this study extend the feasibility and the relevance of GA in a cohort of elderly tumor patients in a central European population. As identified by assessment procedures, a relevant proportion of deficiencies was detected. Factor and correlation analysis revealed six different domains covered by GA instruments, thus forming the basis for efficient application of these instruments in elderly cancer patients. Further research is needed to determine the usefulness of the suggested six-dimension model for the integration of geriatric assessment into oncology practice in the elderly. The methodological approach used in this paper

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might serve as an efficient model for identifying independent domains in future research.

Conflict of interest The authors declare that they have no conflicts of interest.

Reviewers Prof. Lodovico Balducci, H. Lee Moffitt Cancer Center and Research Institute, Senior Adult Oncology Program, Tampa, Florida 33612, United States. Prof. Jean-Pierre Droz, Centre Léon Bérard, Department of Medical Oncology, 28 rue Laennec, F-69373 Lyon cedex 8, France. Dr. Catherine Terret, MD, PhD, Centre Léon Bérard, Department of Medical Oncology, 28 rue Laennec, F-69373 Lyon cedex 8, France.

Acknowledgements This study is supported by Tiroler Verein zur Förderung der Krebsforschung (RS), Österreichische KrebshilfeKrebsgesellschaft Tirol 2006 and 2008 (RS) and Medizinischer Forschungsfonds Tirol (Project No. 174) (RS).

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Biographies R. Stauder received his Doctoral Degree in Medicine in 1981 from the University of Innsbruck and in 2006 received a Master’s Degree in Health Sciences from the University of Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria. He is a specialist in Internal Medicine, a Certified Specialist in Hematology and Oncology and Associate Professor of Medicine at Innsbruck Medical University, Austria. His main clinical and scientific focus lies in geriatric hematology and oncology and in the implementation and evaluation of assessment scores in elderly cancer patients. RS is Member of the EORTC Task Force Cancer in the Elderly, Chairman of the MDS Group and the Geriatric Oncology Group of the Austrian Society for Haematology and Oncology and the National Representative for Austria in the International Society of Geriatric Oncology (SIOG). K. Moser received her degree as doctor of medicine in 2005 from Innsbruck Medical University. Interested in the assessment of cognitive functions she completed her studies with a doctoral thesis at the Clinical Department of Neurology, Innsbruck Medical University, focusing on neuropsychological testing of patients suffering from epilepsy. After working in a family medicine practice she assumed a position as a research associate at Innsbruck Medical University at the Department of Internal Medicine/Hematology and Oncology and now concentrates on geriatric assessment in elderly cancer patients. B. Holzner graduated from Innsbruck University, Faculty of Psychology, in 1994. He earned special degrees in clinical psychology and health psychology (1995 Vienna University) and psychotherapy (1998 Munich University) and has been a staff member of the Division of Psychooncology and Psychoimmunology at the Department of Psychiatry of Innsbruck Medical University since 1994. In 2003 he was named Associate Professor at the Department of Medical Psychology and Psychotherapy and spent several months at the Center on Outcomes, Research and Education in Evanston/Chicago. In the same year he was appointed Associate Director of the Division of Psychooncology with special responsibilities for research. His clinical interests include the psychooncological treatment of cancer patients, focusing on QOL research in oncology including methodological and clinical issues. B. Sperner-Unterweger studied medicine at the University of Innsbruck and received her medical degree in 1984. She is a Specialist in Psychiatry and Neurology and also holds

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a Diploma in Psychosomatic Medicine. In 1993 she spent several months at the Western Psychiatric Hospital in Pittsburgh. In 1994 she finished her training as a Psychotherapist (cognitive behavioral therapy). In 1999 she was named Associate Professor at the Department of Biological Psychiatry in Innsbruck. Since 1993 she has headed the Division of Psychooncology and Psychoimmunology and since 1998 she has also served as Vice-Chair of the Department of Biological Psychiatry of Innsbruck Medical University.

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G. Kemmler is a medical statistician. He received his first degree in mathematics in 1982 and a Ph.D. in statistics in 1990. He has worked as a consulting statistician with the Department of Biostatistics (1986–1992) and with the Department of Psychiatry (since 1993) at Innsbruck Medical University. His main areas of research comprise statistical methods in psychiatric research and methodological aspects of quality of life research, focusing on applications in both psychiatry and oncology.