UvA-DARE (Digital Academic Repository) Decision making in geriatric oncology Hamaker, M.E. Link to publication

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1 UvA-DARE (Digital Academic Repository) Decision making in geriatric oncology Hamaker, M.E. Link to publication Citation for published version (APA): Hamaker, M. E. (2012). Decision making in geriatric oncology General rights It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulations If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. UvA-DARE is a service provided by the library of the University of Amsterdam ( Download date: 13 Jan 2019

2 Frailty screening tools for predicting outcome of a comprehensive geriatric assessment in older cancer patients: a systematic review M.E. Hamaker, J.M. Jonker, S.E. de Rooij, A.G. Vos, C.H. Smorenburg, B.C. van Munster Lancet Oncology 2012;13:e437 e444

3 Abstract Aim: To assess which frailty screening tools demonstrate the best sensitivity and specificity for predicting the presence of impairments on comprehensive geriatric assessment (CGA) in older cancer patients. Method: A systematic search in Medline and Embase and hand search of conference abstracts, for studies on the association between frailty screening tools and CGA in older cancer patients. Results: Literature search identified 4440 reports, of which 22 publications from 14 studies, assessing seven different frailty screening tools, were included in the review. Median sensitivity and specificity of the screening tools for frailty on CGA were respectively: Vulnerable Elders Survey 13 (VES 13) 68%/78%, Geriatric 8 (G8) 87%/61%, Triage Risk Screening tool (TRST, cut off 1+) 91%/±45%, Groningen Frailty Index (GFI) ±50% /±75%, Fried frailty criteria, ±30%/±90%, Barber 59%/79%, and abbreviated CGA (acga) 51%/97%. However, even in case of the highest sensitivity, the negative predictive value was only 60%. Conclusion: G8 and TRST demonstrated the highest sensitivity for frailty, but had a poor specificity and negative predictive value. These findings suggest that for now, it may be beneficial for all older cancer patients to receive a complete geriatric assessment as the currently available frailty screening tools have insufficient discriminative power in selecting patients for further assessment. 184

4 Frailty screening tools in geriatric oncology Introduction Although malignant tumours occur at all ages, cancer disproportionately strikes individuals aged 65 years and older, 1 and the number of elderly cancer patients will increase substantially in the coming decades as a result of increasing life expectancy and ageing of the population. Cancer specialists are faced with the challenge of determining the optimal treatment for these patients, with their heterogeneity in comorbidity, physical reserve, disability and geriatric conditions. For this purpose, two concepts of geriatric medicine are being incorporated in geriatric oncology: the concept of frailty and the comprehensive geriatric assessment. Frailty is considered as a state of decreased physiological reserves, arising from cumulative deficits in multiple physiological systems, resulting in a diminished resistance to stressors. 2,3 As cancer and its treatment both form significant stressors, requiring patients to encroach on their reserves, the concept of frailty appears particularly relevant for older cancer patients. As yet, there is no consensus on its operationalization. The original definition of frailty as formulated by Fried et al. focuses primarily on physical weakness and wasting, but many other definitions and criteria have been postulated, incorporating different aspects of ageing that contribute to diminishing reserves. 4 6 In geriatric oncology, the comprehensive geriatric assessment (CGA) is used to detect disabilities and geriatric conditions that potentially contribute to frailty. A CGA is a systematic procedure used to objectively appraise the health status of older people, focusing on somatic, functional and psychosocial domains, 7 and its value in geriatric medicine has been proven extensively. 8 However, as a CGA is time consuming, research is now focusing on screening tools to separate fit older cancer patients that are able to receive standard cancer treatment based upon the complete treatment schedule, from vulnerable patients that should subsequently receive a CGA to guide tailoring of their treatment regimen. 9 In this context, the sensitivity of a frailty screening tool is considered to be of prime importance; this will allow the treating physician to trust that frail patients will correctly be identified by the screening tool. 10,11 However, to optimize the time saving potential of a two stepped approach, a good specificity of the screening tool is also required to ensure that the number of fit patients incorrectly identified as frail on the screening tool and thus unnecessarily receive a CGA, will be limited. To determine which screening tool best meets both criteria, we performed a systematic review to assess the sensitivity and specificity of frailty screening tools in predicting the presence of impairments on a CGA. 185

5 Methods Search strategy and selection criteria Our aim was to identify cohort studies which investigated the association between an established frailty screening tool and a more complete CGA in cancer patients, independent of age, cancer type or stage of disease. The following search was performed on December 28 th 2011, in both Medline and Embase: ((("Geriatric Assessment"[Mesh]) OR (gfi[tiab] OR groningen frailty index[tiab]) OR (tfi[tiab] OR tilburg frailty index[tiab]) OR (isar[tiab] OR identification seniors at risk[tiab]) OR (G8[tiab]) OR (fried[tiab]) OR (barber[tiab]) OR (edmonton[tiab]) OR (saop[tiab] OR senior adult oncology program[tiab]) OR (triage risk screening tool[tiab]) OR (runciman rowland questionnaires[tiab]) OR (ves 13 OR vulnerable elderly survey[tiab]) OR (abbreviated comprehensive geriatric assessment[tiab] OR acga[tiab]) OR (geriatric assessment*[tiab])) OR ((screening tool*[tiab]) AND (elderl*[tiab] OR geriatri*[tiab] OR old age[tiab]))) AND (("Neoplasms"[Mesh]) OR (neoplasm*[tiab] OR cancer*[tiab] OR tumour[tiab] OR tumours[tiab] OR tumor[tiab] OR tumors[tiab] OR oncolog*[tiab] OR malignan*[tiab])). No language limits or date ranges were applied. In addition, conference abstracts of the scientific meetings from of the American Society of Clinical Oncology (ASCO), European Society of Medical Oncology (ESMO), International Society of Geriatric Oncology (SIOG), American Geriatric Society (AGS) and European Geriatric Medicine Society (EUGMS) were hand searched for studies on CGA in cancer patients to identify additional eligible studies. We defined a frailty screening tool as a tool designed to assess the concept of frailty, irrespective of the population or purpose for which this tool is intended. A CGA was defined as an assessment using validated assessment tools investigating at least three of the following domains: cognitive function, mood/depression, nutritional status, activities of daily living (ADL), instrumental activities of daily living (IADL), comorbidity, polypharmacy, mobility/falls, and/or social support. Studies were not eligible for inclusion in this review if the study cohort included non cancer patients. We also excluded studies if the CGA was only performed in a subgroup of patients selected by the outcome of the frailty screening tool(s). For studies which included more than one screening tool, eligibility was assessed separately for each tool. The titles and abstracts of all studies retrieved by the searches were assessed by one reviewer (MH) to determine which warrant further examination. All potentially relevant articles were subsequently screened as full text by two authors (MH and JJ). If only an abstract was available, an effort was made to find the final report of the study by searching Embase and Medline using the names of first, second and/or final authors as 186

6 Frailty screening tools in geriatric oncology well as key words from the title. Also, in case of insufficient data in the original manuscript, the authors were contacted for additional information, for example on the tools used in the geriatric assessment or the cut off value of the screening tool. Data extraction Data regarding study design and results were independently extracted by two investigators (MH and JJ) for each eligible study. Items that were extracted are the type of study, study setting, study population (cancer type, cancer stage, cancer treatment, the timing of screening), the frailty screening tools used including cut off values, the content of the CGA and the assessment tools used, as well as the outcomes in terms of association between frailty screening tool and CGA. Quality assessment The methodological quality of each of the studies was also assessed independently by two reviewers (MH and JJ), using the QUADAS 2 tool (Quality Assessment of Studies of Diagnostic Accuracy included in Systematic reviews, Appendix 1) as developed and revised by Whiting et al. 12,13 Disagreements among the reviewers were discussed during a consensus meeting and in case of persisting disagreement, the assistance of a third reviewer (BvM) was enlisted. To address the suitability of the CGA to detect frailty, we used the definition formulated by the International Society of Geriatric Oncology, which states that at minimum, a CGA for older cancer patients should include assessment of functional status, cognition and mood. 7 Data synthesis and analysis We summarized the study results to describe our main outcomes of interest. If necessary, sensitivity, specificity, positive and negative predictive values were calculated based on the results listed in the publication, or in case of insufficient published information on additional data obtained from the authors. 187

7 Table 1: Studies on the association between frailty assessment and comprehensive geriatric assessment Publication Patients Author Publication year Abstract(A) or full text (F) Setting/department Study population Number of patients % male Median age in years (range) Baitar A Unclear Various cancer types 135? 77 (66 97) Kellen F Medical oncology/ general practice Various cancer types, irrespective of stage of disease or treatment % 77 (SD 4) Kenis A Medical oncology Kenis A Medical oncology Newly diagnosed cancer or progressive disease, during admission Various cancer types, patients considered for start of chemotherapy Kristjansson A Surgery Pre operative patients with colorectal cancer considered for surgery Luciani F Medical Various cancer types, prior to start oncology first line chemotherapy Mohile 22, F Medical Prostate cancer patients receiving oncology hormonal treatment Molina 2010 F Medical Early stage breast cancer prior to Garrido oncology start chemotherapy Molina 2011 A Medical Garrido 27 oncology Monfardini A Medical oncology 140? 76.5 (SD 5.1) % 76.9 (SD 5.1) 74 46% 80 (71 94) % 76 (70 97) % 78 (70 92) 41 0% 74.5 (SD 5.1) Unclear 58? Not stated Patients with breast cancer newly referred to medical oncologist 150? 76 (70 94) Owusu F Medical oncology Various cancer types, first visit to outpatient clinic with newly diagnosed cancer % 72 (IQR 69 80) Pottel F Radiotherapy Head and neck cancer patients prior to start radiotherapy 51 84% 72 (65 86) Soubeyran A Medical oncology Various cancer types, prior to start of first line chemotherapy % 77 (70 99) Soubeyran 34, A Medical oncology Unclear % 78.2 (70 98) * A more detailed overview of the content of the geriatric assessment can be found in Appendix 3 188

8 Frailty screening tools in geriatric oncology Table 1: Studies on the association between frailty assessment and comprehensive geriatric assessment Screening tool Geriatric assessment (CGA)* Frailty screening tool used (cut off) Cognition Mood ADL IADL Nutritional status Social support Comorbidity Polypharmacy Mobility/falls Cut off value for frailty on CGA (nr of impairments unless otherwise stated) GFI (4+) G8 ( 14) acga (1+)** VES13 (3+) GFI (4+) GFI (4+) G8 ( 14) TRST (1+/2+) TRST (1+) G8 ( 14) Cognitive impairment or 2+ more other impairments Fried (3+) VES 13 (3+) VES 13 (3+) VES 13 (3+) Barber (1+) Fried (3+) VES 13 (3+) VES 13 (3+) ADL dependent, 3+ comorbidities or 1+ severe comorbidities VES 13 (3+) G8 ( 14) VES 13 (3+) G8 ( 14) G8 ( 14) VES 13 (3+) ** In the original acga publications, screening yielded subscores per domain but not an overall score. This cutoff value in this study was defined by its researchers, based on the aggregated results of the subscores. GFI Groningen Frailty Index, G8 Geriatric 8, acga abbreviated comprehensive geriatric assessment, VES13 Vulnerable Elders Survey 13, TRST Triage risk screening tool, (I)ADL instrumental activities of daily living 189

9 Results Characteristics of included studies The literature search yielded 3943 citations (1769 from Medline and 2174 from Embase) and an additional 497 studies on geriatric assessment in cancer patients were identified in conference abstracts. For one of the identified abstracts, the full text publication came out after the search date; however, as this contained additional, useful information, we included this manuscript as well. After exclusion of 1279 duplicates and 3139 studies for other reasons (Appendix 2), a total of 22 publications from 14 studies were included in this review The characteristics of these 14 studies are summarized in Table 1. The first publication is in 2007 but most were published in the past two years For seven studies, full text reports were available, 17,21 26,29 32 but for the seven remaining studies, conference abstracts were the only publications ,18 20,27,28,33 35 Median sample size was 117 patients (range ). Median age of included patients ranged from 72 to 80 years All but two studies 20,30 32 were performed in the medical oncology department. Half of the studies included patients with various cancer types 17 19,21,27,29,33 while two did not elaborate on the type of patients that were included, 27,34,35 the other five studies focused on one cancer type only (two on breast cancer, 24 26,28 and one each on prostate cancer, 22,23 colorectal cancer 20 and head and neck cancer ). Seven different frailty screening tools were assessed: Vulnerable elders survey 13 5 was the most frequently examined (VES 13, 9 studies) followed by the Geriatric 8 36 (G8, six studies), Groningen Frailty Index 4 (GFI, 3 studies), Triage Risk Screening Tool 37 (TRST) and Fried frailty criteria 6 (2 studies each), and the abbreviated CGA 38 (acga) and Barber 24 (one study each). Table 2 gives an overview of the domains these tools focus on, and their relative weight. All tools address functional status, and most (five out of seven tools) also focus on some aspect of psychosocial functioning, but for other geriatric conditions there is much more variation (Table 2). The acga and G8 are the only tools designed specifically for assessment of frailty in older cancer patients (Table 2). The content of the CGA varied from four to eight geriatric conditions (Table 1); the median number of examined conditions was seven All studies included assessment of cognitive function and activities of daily living (ADL), although the method of assessment varied Instrumental ADL functioning was examined in twelve studies, 14 17,19,21 35 mood in ten studies, 14 20,28 35 nutritional status in nine, 14 16,19 21,24 27,30 35 mobility/falls history in six studies 14 16,19,29,33 35 and social support in seven ,18,22 29 Comorbidity was examined in thirteen studies 14 16,18 35 and polypharmacy in eight ,29 Frailty on CGA was defined as the presence of one or more geriatric conditions in four studies 20 22,33 35 and two or more 190

10 Frailty screening tools in geriatric oncology Table 2: Relative weight of geriatric conditions in the frailty screening tools (in % of total points per tool) Geriatric domains GFI 4 G8 36 VES 13 5 acga 38 Fried 6 Barber 24 TRST 37 Functional status 27% 11% 60% 60% 60% ADL impairment 13% 20% 33% IADL impairment 7% 40% 11% mobility/falls 7% 20% Psychosocial domain 40% 11% 40% Cognitive 7% 27% 20% disorder Mood/anxiety 13% 13% Social support 20% 11% Neuro sensory deficits 13% 22% Nutritional status/weight loss 7% 46% 20% Polypharmacy 7% 6% 20% Comorbidity Recent 11% 20% hospitalization Geriatric syndromes 20% Self reported health 7% 11% 10% 20% 11% Age 11% 30% Optimal score * Poorest score * Standard cut off value * Population for which tool was designed Various Cancer patients Communitydwelling elderly Cancer patients No specific population Primary care patients Patients in emergency room * no overall scoring of acga is available; subscores for each geriatric domain are calculated. GFI Groningen Frailty Index, G8 Geriatric 8, VES 13 Vulnerable elders survey 13, acga abbreviated comprehensive geriatric assessment, TRST triage risk screening tool; (I)ADL (instrumental) activities of daily living in eight studies ,18,19,22 27,29 32 The remaining two studies applied other definitions, assigning different weights to the various assessed conditions (Table 1). 17,28 Study populations showed a wide variation in the prevalence of frailty as diagnosed by the CGA; a median of 68% of patients was considered frail (range 28 94%, Table 3) This wide range cannot be explained solely by differences in the cut off used for the definition of frailty on CGA, as in studies using the cut off of 1+ prevalence of frailty ranged from 28 to 80% 20 22,33 35 while in studies using a cut off of 2+, the range was 43% to 88% ,18,19,22 27,29 32 According to frailty screening tools, the median prevalence of frailty was 49% (range 12 83%)

11 Quality assessment Results of the quality assessment can be found in Figure 1. Reviewer agreement was over 95% for all aspects. For patient selection, the risk of bias was generally considered low, and little concerns existed about the applicability of selection criteria. Due to the lack of information on the independent scoring of the frailty screening tool and the CGA, the risk of bias was frequently unclear for both the index test as well as the reference test. Variation in the content of the CGA resulted in some concerns about the applicability of study results and may also have introduced risk of bias. Flow and timing of the studies yielded few concerns. Full results of the quality assessment can be found in Appendix 1b. Figure 1: Quality assessment of included studies, using the QUADAS 2 assessment tool (Appendix 1a). 13 The complete assessments per study can be found in Appendix 1b. 192

12 Frailty screening tools in geriatric oncology Frailty screening tools vs. comprehensive geriatric assessment Table 3 gives an overview of the sensitivity and specificity of the frailty screening tools compared to frailty as detected by CGA, while Figure 2 demonstrates the relationship between sensitivity and false positives per screening tool. For the VES 13, sensitivity ranged from 39% to 88% with a median of 68%. 17,21 32,34,35 Thus, a median of 32% of frail patients were not recognized as frail by the VES 13. The specificity was better, ranging from 62% to 100%, with a median of 78%. Thus, the VES 13 yielded 22% false positives. For the G8, the sensitivity ranged from 77% to 92%, with a median of 87% but the specificity ranged from 39% to 75%, with a median of 61% ,18,19,30 35 The TRST (using a cut off of 1+) showed a sensitivity of 91% with a specificity of between 43 and 50%. 18,19 For the GFI, sensitivity ranged from 39% to 62%, and the specificity was between 69% and 87% For the Fried frailty criteria, the sensitivity was between 25% and 37%, with a specificity of 86% to 96%. 20,27 Table 3: Sensitivity and specificity of frailty screening tools for outcome of (summarized) comprehensive geriatric assessment (CGA) Screening tool (cut off) Study % frail on screening tool % frail on CGA Sensitivity (%) Specificity (%) Positive predictive value (%) Negative predictive value (%) acga (1+) Kellen (2010) Barber (1+) Molina Garrido (2010) Fried (3+) Kristjansson (2008) Molina Garrido (2011) Baitar (2011) Kenis (2009) G8 ( 14) Kenis (2011) Pottel (2011) Soubeyran (2008) Soubeyran (2011) 34, Baitar (2011) 14, GFI (4+) Kellen (2010) Kenis (2009) TRST (1+) Kenis (2009) Kenis (2011) TRST (2+) Kenis (2009) Kellen (2010) Luciani (2010) Mohile (2007) 22, Molina Garrido (2010) VES 13 (3+) Molina Garrido (2011) Monfardini (2010) Owusu (2010) Pottel (2011) Soubeyran (2011) 34, GFI Groningen Frailty Index, G8 Geriatric 8, VES 13 Vulnerable elders survey 13, acga abbreviated comprehensive geriatric assessment, TRST triage risk screening tool 193

13 Figure 2: Sensitivity and 1 specificity of the screening tools for predicting outcome of comprehensive geriatric assessment GFI Groningen Frailty Index, G8 Geriatric 8, VES 13 Vulnerable elders survey 13, acga abbreviated comprehensive geriatric assessment, TRST triage risk screening tool Interestingly, as the prevalence of frailty in most study populations was high, even the screening tools with the highest sensitivity to frailty still yielded negative predictive values of around 60% (Table 3). This means that four out of every ten patients considered fit after frailty screening, will be diagnosed as frail after CGA. Frailty screening tools vs. individual geriatric conditions Although frailty screening tools are generally used to predict overall frailty, a few studies have addressed the association between these tools and individual geriatric conditions (Table 4); four studies addressed the latter association for VES 13, 17,22,23,29 32 while one study each looked at acga, 17 GFI 17 and G Comparison of results is compromised, however, by the different methods of presentation of the data. Overall, VES 13 appears to be most strongly associated with ADL and IADL functioning (area under the curve (AUC) between 0.81 and 0.91, sensitivity between 67% and 83% and specificity between 61% and 89%.) 17,22,23,29 32 Association between VES 13 and cognitive disorders, impaired mobility and malnutrition was fair (AUC , and

14 Frailty screening tools in geriatric oncology Table 4: Association between screening tools and individual geriatric domains Screening tool Study Cognition Mood ADL IADL Nutritional status Comorbidity Social support Mobility Polypharmacy Sens 23% AUC 0.73 AUC 0.78 AUC 0.71 AUC 0.67 AUC Sens 47% Sens 75% AUC 0.66 AUC acga Kellen Sens 69% Sens 97% Sens 92% (2010) 17 Spec 100% Spec 92% Spec 47% Spec 69% G8 Pottel AUC 0.74 AUC (2011) GFI Kellen Sens 39% (2010) 17 Spec 76% Spec 86% VES 13 Kellen (2010) 17 Sens 76% Sens 67% Spec 63% Spec 89% Mohile Sens 83% Sens 76% Sens 76% Sens 33% Sens 70% (2007) 22,23 Spec 58% Spec 61% Spec 68% Spec 64% Spec 46% Spec 67% Owusu AUC 0.81 AUC 0.81 AUC 0.91 AUC 0.73 AUC 0.57 AUC 0.72 ( Pottel (2011) AUC 0.79 AUC 0.74 AUC 0.87 AUC 0.86 AUC 0.78 AUC 0.70 AUC 0.87 acga abbreviated comprehensive geriatric assessment, G8 Geriatric 8, GFI Groningen frailty index, VES 13 Vulnerable Elders Survey 13; AUC area under the curve respectively) 22,23,29 32 G8 showed a strong association with malnutrition (AUC 0.95), but was of lesser value for predicting the presence of other geriatric conditions acga showed a strong association with ADL and IADL impairment (sensitivity 97% and 92%, specificity 47% and 69% respectively), but the sensitivity for cognitive dysfunction or depressive symptoms was low (23% and 69% respectively). 17 GFI demonstrated poor sensitivity for functional impairment (ADL impairment 47%, IADL impairment 39%) but reasonable specificity (76% and 86% respectively). 17 Discussion A useful frailty screening tool in geriatric oncology should have a high sensitivity, thus allowing the assessor to trust that those patients deemed fit actually are fit, and a sufficient specificity so that the time consuming process of a full CGA is optimally utilized. 10,11,39 In this systematic review on the discriminative power of frailty screening tools for outcome of full CGA, we found that those tools with the highest sensitivity lacked specificity and vice versa. In addition, even for the screening tools with the highest sensitivity, the negative predictive value (i.e. the proportion of patients considered fit on the screening tool that were also considered fit after full CGA) was around 63%, meaning over a third of patients were unjustly considered fit after frailty screening. 195

15 Given the content of the frailty screening tools and the population and purpose for which they were developed (Table 2), the lack of sensitivity of some of these screening tools when used to predict outcome of CGA is hardly surprising. For example, the VES 13 5 and Fried frailty criteria 6 focus strongly on functional status (Table 2). Therefore, it is not surprising that these tools are not very successful in identifying impairments in other geriatric domains. For other screening tools, such as the GFI, the lack of discriminative power could be explained by the fact that they were designed to diagnose frailty in a different patient population than that in which it is being used in geriatric oncology (Table 2). In fact, most of the screening tools that are being used in geriatric oncology were not designed or validated for this particular setting; only the G8 and acga developed specifically for use in older cancer patients. As the acga was designed to identify which individual geriatric domains require further assessment, the lack of sensitivity for overall frailty (median 51%) as well as for two of the four individual domains for which it was designed (Table 4) is disappointing. Ultimately, the G8 and the TRST developed to assess functional impairment in older patients admitted to the emergency department 37 had the highest sensitivity for frailty on CGA (87 and 91% respectively) but both lacked specificity (61% and 45% respectively). Thus, no screening tool currently used in geriatric oncology combined adequate sensitivity and specificity. In addition, for tools with the highest sensitivity, the percentage of patients diagnosed as frail after screening was around 70%, and based on the negative predictive value of these tools one third of the remaining 30% was incorrectly diagnosed as fit. Considering these findings, the question rises whether there is any benefit in a twostepped approach in which a CGA is preceded by a screening tool. The time saving potential of this approach will be limited if the prevalence of frailty is high, and potentially does not outweigh the risk of incorrectly identifying patients as fit and delivering care asusual where a more cautious approach would have been better. Another aspect for which the use of a screening tool prior to CGA could be beneficial is to identify which geriatric domains require further assessment; this could save time by allowing the CGA to be limited to those domains only. Several studies in this review addressed this issue (Table 4); however, the available data are limited. In addition, these studies examined the association between the entire screening tool and a specific geriatric domain while it would be more useful to assess the sensitivity of each individual screening question for the presence or absence of the specific geriatric conditions that the question inquires after. This aspect warrants further exploration in future research. This systematic review provides a valuable overview of all currently available evidence on the use of frailty screening tools in geriatric oncology but it also has several limitations. First of all, we limited our search to studies performed in older cancer patients, thus excluding available evidence from other patient populations. However, the prevalence of 196

16 Frailty screening tools in geriatric oncology geriatric conditions and frailty will differ greatly in various contexts and the discriminative power of frailty screening tools should therefore be assessed in the context that it will be used in. Another limitation of this review is that no full text reports have been published for half of the included studies, and we had to rely on conference abstracts as the only source of information on the execution and results of the study. In particular, this limited our ability to analyse the predictive value of the frailty screening tools for individual domains. Moreover, the content of the CGA differed considerably between studies, as did the cut off value that was used to define frailty. The definition of frailty that is used will influence the prevalence of frailty in a study population and similarly the sensitivity and specificity of screening tools in predicting that frailty. This lack of golden standard for assess frailty assessment decreased the comparability of study results and subsequently hampered the execution of a formal meta analysis, thus leaving uncertainty about the relative quality of the different screening tools for detecting frailty in older cancer patients. In 2005, the International Society of Geriatric Oncology recommended that, at minimum, frailty assessment for older cancer patients should include an evaluation of functional status, cognition and mood. 39 In wake of growing evidence that geriatric conditions, such as nutritional status, polypharmacy, comorbidity and social support may also be significant for older cancer patients, perhaps an update of these recommendations should be undertaken. Moreover a consensus in the scales to use, including their cut off values, would result in greater uniformity in clinical practice and research, and allow for better comparison between studies and patient populations. Ultimately, establishing whether a patient is fit or frail is not a goal in itself, but a method for optimizing and tailoring oncologic and non oncologic treatment in elderly cancer patients. Therefore, future research should focus on a more elaborate exploration of the value of frailty and individual geriatric conditions for predicting and improving clinical outcomes such as quality of life, survival, treatment tolerance and functional decline. In conclusion, although the Geriatric 8 and Triage Risk Screening Tool demonstrated the best sensitivity for frailty on full CGA in older cancer patients, they had a poor specificity and negative predictive value. Perhaps it will be possible to develop targeted screening tools with better sensitivity and specificity once the relative importance of individual geriatric domains and the benefit of appropriate interventions and follow up are fully elucidated in this patient population. Until such a time, it may be beneficial for all older patients to receive a complete geriatric assessment, since the two stepped approach using frailty screening tools to select patients for CGA has insufficient discriminative power. 197

17 Appendix 1a: Quality Assessment of studies of Diagnostic Accuracy included in Systematic reviews 2 (QUADAS 2) tool 12,13 Domain 1: Patient Selection Risk of Bias: Could the selection of patients have introduced bias? 1: Was a consecutive or random sample of patients enrolled? 2: Was a case control design avoided? 3: Did the study avoid inappropriate exclusions? Applicability: Are there concerns that the included patients and setting do not match the review question? Domain 2: Index Test Risk of Bias: Could the conduct or interpretation of the index test have introduced bias? 1: Were the index test results interpreted without knowledge of the results of the reference standard? 2: If a threshold was used, was it prespecified? Applicability: Are there concerns that the index test, its conduct, or its interpretation differ from the review question? Domain 3: Reference Standard Risk of Bias: Could the reference standard, its conduct, or its interpretation have introduced bias? 1: Is the reference standard likely to correctly classify the target condition? For this purpose, we used the definition formulated by the International Society of Geriatric Oncology, which states that at minimum, a CGA for older cancer patients should include assessment of functional status, cognition and mood. 40 2: Were the reference standard results interpreted without knowledge of the results of the index test? Applicability: Are there concerns that the target condition as defined by the reference standard does not match the research question? Domain 4: Flow and Timing Risk of Bias: Could the patient flow have introduced bias? 1: Was there an appropriate interval between the index test and reference standard? 2: Did all patients receive the same reference standard? 3: Were all patients included in the analysis? 198

18 Frailty screening tools in geriatric oncology Appendix 1b: Overview of quality assessment according to the QUADAS 2 tool per study Author Patient selectio n Risk of bias Concerns about applicability Index Reference Flow and Patient Index test test timing selection test Baitar (2011) Unclear Unclear Unclear Unclear Low Low Low Kellen (2010) 17 Low Unclear Unclear Low Low Low Low Kenis (2009) 18 Low Low Low Low Low Low Low Kenis (2011) 19 Low Unclear Unclear Low Low Low Low Kristjansson (2008) 20 Low Unclear Unclear Low Low Low Low Luciani (2010) 21 Low Unclear Unclear Low Low Low Low Mohile (2007) 22,23 Low High High Low Low Low High Molina Garrido (2010) Low Unclear High Low Low Low High Molina Garrido (2011) 27 Unclear Unclear High Low Unclear Low High Monfardini (2010) 28 Low Low Low Low Low Low Low Owusu (2010) 29 Low Unclear Unclear Low Low Low Low Pottel (2011) Low Unclear Unclear Low Low Low Low Soubeyran (2008) 33 Low High Unclear Unclear Low Low Low Soubeyran (2011) 34,35 Low Unclear Unclear High Low Low Low Reference test Appendix 2: Search and study selection All studies n= 4440 Medline n= 1769 Embase n= 2174 Conference abstracts n= 497 Duplicates n= 1279 Exclusion n= 3139 Not original research n= 747 Not oncology n= 444 No comprehensive geriatric assessment (CGA) n= 1340 No screening tool n= 566 No association screening tool with CGA n= 22 Non cancer patients included n= 8 CGA not performed in all patients n= 3 Substantial overlap with another publication n= 2 Insufficient data for analysis n= 5 Retrospective tool development n= 2 Inclusion: 22 publications from 14 studies 199

19 Appendix 3: Complete overview of comprehensive geriatric assessment per study Author Frailty screening tool used (cut off) Cognition Mood ADL IADL GFI (4+) acga (1+) GFI (4+) TRST (1+) MMSE GDS Barthel MNA CIRS G + Lawton Social VES 3 (3+) SPMSQ Baitar MMSE GDS Katz Lawton TUG MOS Charlson (2011) G8 ( 14) SSS Kellen MMSE GDS Barthel Lawton (2010) 17 VES13 (3+) GFI (4+) Kenis MMSE GDS Katz + + CIRS G + Age (2009) 18 G8 ( 14) TRST (1+/2+) Kenis MMSE GDS Katz Lawton MNA Fall Charlson + Fatigue (2011) 19 G8 ( 14) history (Mob T) Kristjansson Fried (3+) (2008) 20 Luciani VES 3 (3+) MMSE Katz MNA CIRS G + (2010) 21 status Mohile Katz Lawton MOS Charlson + SPPB (2007) 22,23, Pfeiffer SSS Molina Garrido (2010) Molina Garrido (2011) 27 VES 3 (3+) Barber (1+) Fried (3+) VES 13 (3+) Nutrition Mobility/falls Social Comorbidity Pfeiffer Barthel Lawton NSI Gijon Charlson + Pfeiffer Barthel Lawton NSI Gijon Charlson + Monfardini (2010) 28 VES 3 (3+) MMSE GDS Katz Lawton CIRS G + Owusu MOS Charlson + (2010) 29 history SSS Pottel MMSE GDS Katz Lawton MNA Tinetti CIRS G (2011) VES 3 (3+) Soubeyran Polypharmacy Others Visual/hearing impairment (2008) 33 (QLQ C30) G8 ( 14) MMSE GDS Katz Lawton MNA TUG CIRS G Quality of life Soubeyran (2011) 34,35 G8 ( 14) VES 3 (3+) MMSE GDS Katz Lawton MNA TUG CIRS G GFI Groningen Frailty Index, G8 Geriatric 8, VES 13 Vulnerable elders survey 13, acga abbreviated comprehensive geriatric assessment, TRST triage risk screening tool + assessed without the use of a specific assessment tool (I)ADL instrumental activities of daily living, MMSE mini mental state examination, SPMSQ short portable mental status questionnaire, GDS geriatric depression scale, MNA mini nutritional assessment, NSI nutrition screening initiative TUG Timed up and go, MOS SSS medical outcomes study social support survey CIRS G cumulative illness rating scale geriatric, SPPB short physical performance battery QLQ C30 quality of life questionnaire 200

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