ORIGINAL ARTICLE. Monica P. Parmar & Tara Swanson & R. Thomas Jagoe

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1 Support Care Cancer (2013) 21: DOI /s ORIGINAL ARTICLE Weight changes correlate with alterations in subjective physical function in advanced cancer patients referred to a specialized nutrition and rehabilitation team Monica P. Parmar & Tara Swanson & R. Thomas Jagoe Received: 14 October 2012 / Accepted: 11 February 2013 / Published online: 26 February 2013 # Springer-Verlag Berlin Heidelberg 2013 Abstract Purpose The aim of this study is to assess whether shortterm weight gain correlates with improvements in subjective markers of quality of life and physical function in patients referred to a clinic for management of cancer cachexia. Methods A retrospective review of the records of 306 patients referred to a specialized multi-disciplinary supportive care team with particular interest in treating cancer cachexia. Weight changes between each of the first three clinic visits, were correlated with the corresponding changes in patientrated performance status, perceived strength and quality of life. In a second cohort of 56 patients, the correlation between perceived strength and quality of life was re-tested using a more detailed quality of life tool. Results Even over short time intervals positive correlations were observed for weight change vs. change in patient-rated performance status (R s >0.15, P<0.05), and for changes in perceived strength vs. quality of life (R s >0.33, P<0.001). The correlation between changes in patient-rated strength and quality of life was consistent across all subgroups studied and was reproducible when using a different, validated, quality of life tool (FAACT) in a second independent patient cohort. Conclusions Weight gains are associated with subjective improvements in physical functioning, and changes in perceived physical strength are consistently correlated with quality of life. Electronic supplementary material The online version of this article (doi: /s ) contains supplementary material, which is available to authorized users. Monica P. Parmar and Tara Swanson contributed equally to this work M. P. Parmar : T. Swanson : R. T. Jagoe (*) Segal Cancer Centre, Lady Davis Institute for Medical Research, McGill University, Jewish General Hospital, 3755 Cote Ste Catherine, Montreal, Quebec H3T 1E2, Canada thomas.jagoe@mcgill.ca Keywords Body weight. Cancer cachexia. Quality of life. Strength. Performance status Background Weight loss is common in patients with advanced cancer, and is a powerful and independent marker of poor prognosis in the vast majority of patients studied [1 3]. Reduced performance status often accompanies weight loss, but performance status has independent prognostic significance for cancer patients [2, 4, 5]. Not only do cancer patients with weight loss, and particularly those with low skeletal muscle mass [6], have more frequent reductions in functional status [7 9], they also have increased rates of treatment toxicity which limits effective cancer treatment delivery [1, 3, 10]. Over recent years, there has been renewed interest in cancer cachexia: a complex clinical syndrome that encompasses the features of weight loss, muscle wasting and often leads to reduced physical performance [11]. In addition to such impairments in objective measures, patients with cancer cachexia also suffer nutritional symptoms such as anorexia, physical function-related symptoms, including dyspnea and fatigue [12], as well as poor quality of life [13, 14]. Effective pharmacological treatments for cancer-related weight loss, muscle wasting, and many nutrition-related symptoms (e.g. anorexia) or function-related symptoms (e.g. fatigue) are still lacking. However, given the increasing numbers of patients undergoing active treatment or surviving after cancer treatment, such symptoms are increasingly common and pose considerable management difficulties. Recent studies have investigated the role of non-pharmacological interventions such as nutritional support and exercise training, which appear to be both feasible and effective at every stage of the cancer disease trajectory. Though nutritional interventions alone are not sufficient to correct all cancer-related

2 2050 Support Care Cancer (2013) 21: weight loss or cancer cachexia [11], establishing and maintaining adequate nutrition is still an essential, and often neglected, prerequisite for success of any other treatment. At one extreme where weight loss and deficient nutritional intake occur in the context of advanced or untreatable solid tumours, some patients will have improved energy balance and gains in weight and functional capacity with use of aggressive nutritional support such as total parenteral nutrition (TPN) [15]. However, a number of studies have shown that early nutritional intervention with dietary advice and, if needed, oral supplements, result in better nutritional status, symptoms, function and quality of life during treatments such as radiotherapy [16, 17]. However, these benefits cannot be generalized to all cancer patients [18]. Similarly, a number of studies have shown that exercise training can also improve physical function, symptoms and quality of life during [19 21], and after cancer treatment [22], in some groups of patients. Nevertheless, in cancer patients with multiple symptoms, and various potential alterations in metabolism and body composition, it is difficult to predict how physical function or activity-related symptoms will be affected by weight changes [23]. This issue remains an important one in patients with advanced incurable cancer, many of whom may have lost weight: if weight gain does not lead to improved symptoms, quality of life, or performance status, it may not be appropriate to plan nutritional interventions aiming for weight gain, or to use weight gain itself as a marker of treatment success. The McGill Cancer Nutrition-Rehabilitation Program clinic at the Segal Cancer Centre, Jewish General Hospital (CNR-JGH clinic) in Montréal, is a multi-disciplinary team that specifically addresses the clinical needs of patients with cancer referred with weight loss, anorexia and reduced physical function. As a group, these patients often have severe nutritional and functional impairment as well as a range of related symptoms, and the CNR-JGH clinic uses a comprehensive interdisciplinary approach to assess and, where possible, control symptoms, combined with individualized dietary interventions and physical rehabilitation. This is in line with generally accepted advice that symptom control is a pre-requisite for successful objective improvements in cancer cachexia treatment [24], and the need for multi-disciplinary approaches to combat this multifactorial condition [25]. Weight and symptoms are monitored closely and treatment plans include strenuous efforts to correct weight loss in the CNR-JGH clinic. However, we wanted to confirm whether weight gain, between clinic visits, is accompanied by simultaneous improvements in selected functional symptoms and quality of life. In particular, we wanted to test whether associations between weight gain and improved functional symptoms were seen in all patients, or restricted to certain subgroups (e.g. those not receiving chemotherapy). In addition, we specifically wanted to determine whether any such correlations were reproducible over successive clinic visits. In this way, we hoped to be able to identify robust and clinically useful short-term indicators of successful nutritional and functional rehabilitation to guide treatment planning in the future. Methods A quantitative retrospective study was performed using data collected between 2002 and 2010 for the first three visits of patients attending the CNR-JGH clinic. Patients were referred to the CNR-JGH clinic for consultation by their treating oncology teams at the Jewish General Hospital: an urban university teaching hospital in Montréal, Québec, Canada. The CNR-JGH clinic delivers medical, nursing, nutritional and physical rehabilitation interventions to address weight loss and associated symptoms, including reduced functional status. Patients were included where complete data were available to perform the primary analysis, namely weight, self-assessed performance status, perceived level of strength and quality of life (defined in detail below) for either the first two, or the first three visits to the CNR-JGH clinic. Patients were excluded if either visit interval (between visits 1 and 2, or 2 and 3) was less than 3 weeks or greater than 24 weeks. The study was approved by the Research Ethics Committee of the Jewish General Hospital. Data collection Three key function-related symptoms recorded at each visit were used for this study. Self-assessed performance status (PS-pt) taken from box 4 of the Patient-Generated Subjective Global Assessment (PG-SGA) [26] tool (range 0 3, where 0 is unrestricted and 3 is restricted to bed or chair for the majority of the day) (Electronic supplementary material (ESM) Fig. 2A). Self-rated assessments of overall quality of life and strength were two question items on a larger questionnaire modeled on the Edmonton Symptom Assessment System [27] that patients completed at each visit. Responses to questions on quality of life (QoL Q2 ) and strength (Str Q4 ) were recorded using independent numeric response scales ranging from 0 ( excellent quality of life or normal strength )to10( very bad quality of life or extremely weak ) (ESM Fig. 2B). In clinic, height was measured to the nearest 0.5 cm and weight was measured on beam balance or electronic scales to nearest 0.1 kg in normal indoor clothing without shoes. Body mass index (BMI) was calculated from weight (kilogram)/height (meter) 2. Other descriptive data including tumour type, stage, results of blood tests and chemotherapy treatment were also recorded in the clinic chart and confirmed in the hospital laboratory and central pharmacy records respectively. Because of the strong association between

3 Support Care Cancer (2013) 21: systemic inflammation and poor prognosis, weight loss, and more severe symptoms [28, 29], the C-reactive protein (CRP) values were recorded where these were available from blood tests taken within one week of the clinic visit. Chemotherapy status was also recorded given the direct relevance of this type of treatment to both symptoms and weight changes. A patient was deemed to be on chemotherapy if the date of the clinic visit fell within one cycle length (typically 3 weeks) of the beginning of their latest chemotherapy treatment cycle. Chemotherapy treatment regimes were coded as one of three categories: (1) minimum of twoagents including at least one given intravenously (A), (2) single intravenous agent only (B), and (3) oral chemotherapy only (C). Chemotherapy treatment history was recorded as the line number of the most recent chemotherapy received at the time of the CNR-JGH clinic, to identify patients who had required multiple lines of chemotherapy, indicating recurrent disease. The correlation between changes in Str Q4 (Fig. 2B) and quality of life measured using the Functional Assessment of Anorexia/Cachexia Therapy (FAACT) (version 4) questionnaire [30] was assessed in a second independent cohort of new patients at their first and second CNR-JGH clinic visits between 2010 and The FAACT tool has been validated in cancer patients and is sensitive to clinically relevant changes in performance status. Furthermore this tool has specific relevant psychometric properties in patients with cachexia: namely the anorexia cachexia sub-domain scores can improve in response to treatment for anorexia, even when overall performance status may be deteriorating [30]. FAACT scores (including a standardized correction for missing responses) were expressed as percentage maximum for the total and each of the five sub-scales: physical, functional, social, emotional well-being and anorexia cachexia. Statistical analysis Change in weight as percentage (Δ% Wt), change in patient-reported performance status (ΔPS-pt), Str Q4 (ΔStr Q4 ), and QoL Q2 (ΔQoL Q2 ) were calculated for both the first and second visit intervals (between visits 1 and 2, and visits 2 and 3). The correlation between weight change (Δ% Wt) and the between-visit changes in the three selfrated scores (ΔPS-pt, ΔStr Q4, ΔQoL Q2 ) were performed using Spearman s method. To aid interpretation and presentation, the scores derived from the visual analogue scale (0 10) were divided into clinically relevant sub-categories: good 0 3, moderate 4 6, poor 7 10 [31]. Similarly, weight change was categorized as: weight gain (WG) if change >1.5 %, weight stable (WS), and weight loss (WL) if change > 1.5 %. These thresholds were adopted to correspond to weight change of approximately 1 kg in either direction, which exceeds the mean anticipated diurnal variation in body weight (0.5 kg) in healthy individuals [32]. For simplicity, all change values were calculated to ensure that a positive change indicated a gain or improvement in weight or symptoms respectively. In the second cohort correlation was performed using ΔStr Q4 and change in percentage maximum for total FAACT score (ΔTotal%) and physical (ΔP%), functional (ΔF%), social (ΔS%), emotional (ΔE%) well-being, and anorexia cachexia (ΔAC%). Analysis of covariance was performed with ΔStr Q4 as the dependent variable, and ΔQoL Q2 and initial QoL Q2 subcategory as explanatory variables. Comparison of regression models with and without the factors under study was performed using analysis of variance. All statistical analysis was completed using R version 2.15 [33]. Results A total of 306 patients attending at least two CNR-JGH clinic visits were included, this represents approximately 64 % of all patients who attended at least two visits during this period. The majority had non-small cell lung cancer (NSCLC) (59 %), followed by gastrointestinal (13.7 %), small cell lung cancer (7.8 %), breast (3.9 %), haematological (3.9 %). The overall mean age was 64.2 years and 48 % were females (Table 1). One hundred seventy-five patients had the necessary minimum data for all three of their first visits to the CNR-JGH clinic (56 % of all patients attending three or more visits with CNR-JGH). The remaining 131 contributed data only for their first two visits, either because they did not attend, or did not have minimum required data recorded, for subsequent visits. The median interval between visits was weeks (Table 1). Of the patients, 30.7 % had raised CRP levels ( 10 mg/l) at visit 1, but 37 % of NSCLC and 50 % of patients with other tumours, did not have CRP measured within a week of their first visit. Survival data was collected for 98 % of the sample, and at the census date in February 2010, 188 (61 %) of patients had died and the median survival from the date of their first visit was 48.1 weeks (Table 1). Data on tumour stage was available in 238 (78 %) patients: 205 (67 %) had advanced stage (III or IV) disease (Table 2). Analysis of chemotherapy history revealed that 124 (40.5 %) had not received chemotherapy before their first visit to CNR-JGH clinic, and only 8 (3 %) had commenced a third-line treatment regimen (Table 2). The proportion of patients on chemotherapy at the time of their clinic visits were 39, 46, and 40 % for visits 1, 2, and 3 respectively. Of those patients receiving chemotherapy 78, 77, and 60 % were in group A for visits 1, 2, and 3 respectively. Average prior weight loss for patients attending the CNR- JGH clinic is 1.0 kg (1.2 %) in 6 weeks preceding first visit

4 2052 Support Care Cancer (2013) 21: Table 1 Demographic characteristics of patients attending the CNR-JGH clinic Tumour types All Non-small cell lung cancer Other cancers Number of patients N (%) 306 (100) 182 (59.4) 124 (40.6) Gender N (%) Female 146 (47.7) 84 (46.2) 62 (50.0) Male 160 (52.3) 98 (53.8) 62 (50.0) Age (years) Mean (SD) 64.2 (12.1) 65.2 (11.4) 62.7 (12.8) Maximum visits per patient N (%) (42.8) 73 (40.1) 58 (46.8) (57.2) 109 (59.9) 66 (53.2) Visit interval length (weeks) Median (IQR) Visit (4.4) 6.0 (4.0) 6.0 (4.7) Visit (4.4) 6.4 (4.0) 7.4 (5.0) C-reactive protein (mg/l) N (%) Low (<10) 82 (26.8) 62 (34.1) 32 (25.8) High ( 10) 94 (30.7) 52 (28.6) 30 (24.2) Unknown 130 (42.5) 68 (37.4) 62 (50.0) Survival (weeks) Median (IQR) 48.1 (58.5) 50.0 (75.2) 47.0 (42.0) and 6.6 kg (8.8 %) in the 6 months preceding their first visit (data from an over-lapping cohort of 360 new patients, ). On this basis one would expect an average overall weight loss of approximately 2 kg over the first three visits (12 weeks). Instead the current data show that those patients attending the CNR-JGH clinic had no change in mean weight and body mass index (BMI) at the first three visits (Table 3). Calculating individual patient weight changes revealed: median (IQR) weight change was 0.05 (3.3) kg between visits 1 and 2, and 0.00 (3.5) kg between Table 2 Tumour stage and chemotherapy status at first visit to CNR-JGH clinic Tumour types All Non-small cell lung cancer Other cancer Notes: cancer stage: Early/limited stage I or II, Advanced stage III or IV; last recorded chemotherapy line is the maximum that the patient is known to have started (whether currently being treated or not); currently on chemotherapy: a patient was categorized as on chemotherapy if within one cycle length of the beginning of their last chemotherapy treatment; chemotherapy regime: A=on at least two agents including at least one i.v., B=onone agent i.v.; C=on oral agent only Stage N (%) Early/limited 33 (10.8) 18 (9.9) 15 (12.1) Advanced 205 (67.0) 159 (87.4) 46 (37.1) Not recorded 68 (22.2) 5 (2.7) 63 (50.8) Latest chemotherapy line N (%) (40.5) 90 (49.5) 34 (27.4) (41.2) 65 (35.7) 61 (49.2) 2 21 (6.9) 7 (3.8) 14 (11.3) >2 8 (2.6) 3 (1.6) 5 (4.0) Unknown 27 (8.8) 17 (9.3) 10 (8.1) Currently on chemotherapy? N (%) Y 118 (38.6) 64 (35.2) 54 (43.5) N 161 (52.6) 101 (55.5) 60 (48.4) Unknown 27 (8.8) 17 (9.3) 10 (8.1) Current chemotherapy type N (%) A 92 (78.0) 52 (81.3) 40 (74.1) B 18 (15.3) 6 (9.4) 12 (22.2) C 8 (6.8) 6 (9.4) 2 (3.7)

5 Support Care Cancer (2013) 21: Table 3 Weight, body mass index, symptom scores and quality of life at each visit subdivided by tumour category Notes: Tumour type: NSCLC or other. Performance status (PSpt): 0 1=good; 2 3=impaired. QoL Q2 scores: 0 3=good; 4 6= moderate; 7 10=poor *P<0.05, **P<0.01 for NSCLC vs Other; P=0.03, P<0.001 for visit 1 vs 2 Visit (N=306) (N=306) (N=175) Weight (kg) Mean (SD) 67.1 (15.9) 66.8 (15.6) 67.6 (14.8) NSCLC 68.6 (15.1) 68.3 (14.9) 69.4 (14.4)* Other 64.9 (16.7) 64.7 (16.4) 64.4 (14.9) Body mass index (kg/m 2 ) Mean (SD) 24.4 (5.2) 24.3 (5.1) 24.2 (4.5) NSCLC 25.0 (4.8)* 24.8 (4.7)* 24.9 (4.4)** Other 23.6 (5.6) 23.5 (5.5) 23.0 (4.5) Performance status (PS-pt) Mean (SD) 1.48 (0.95) 1.28 (0.93) 1.20 (0.92) NSCLC 62/38 70/30 68/32 Other Good/impaired (%) 59/41 69/31 78/23 Strength (Str Q4 ) Mean (SD) 5.18 (2.48) 4.51 (2.54) 4.37 (2.47) NSCLC Good/moderate/poor (%) 26/42/31 34/46/20 40/42/17 Other 23/41/36 39/35/27 30/41/29 QoL (QoL Q2 ) Mean (SD) 4.11 (2.59) 3.76 (2.37) 3.65 (2.44) NSCLC Good/moderate/poor (%) 42/43/15 48/38/13 56/33/11 Other 44/31/25 48/39/13 45/36/18 visits 2 and 3. However, NSCLC patients had significantly greater BMI than those with other tumour types at each visit (Table 3). At the first visit, approximately 40 % of patients reported impaired performance status (PS-pt score 2 3), 33 % reported poor perceived strength, and 20 % had poor quality of life. There was a significant improvement in each of these symptoms between visits 1 and 2, but no change in the group mean values between visits 2 and 3. Furthermore, these changes were similar for those with NSCLC or other types of tumours (Table 3). Correlation between weight change and change in PS-pt, Str Q4,andQoL Q2 for each individual patient, was then performed (Table 4). For correlation analysis, weight change was expressed as percent of weight at the beginning of each visit interval (Δ% Wt). The only significant correlations that were reproducible in both visit intervals were: (a) Δ%Wt vs ΔPS-pt (R>0.15, P<0.05) and (b) a stronger correlation between ΔStr Q4 vs ΔQoL Q2 (R>0.33, P<0.001). The consistency of these correlations was tested within different subgroups namely: gender, cancer type (NSCLC or Other), BMI (> or the median value of 24 kg/m 2 ), and whether on or off chemotherapy treatment. The significant positive correlation between ΔStr Q4 and ΔQoL Q2 was reproduced at every clinic visit and in all subgroups examined. However, the correlation between Δ% Wt and ΔPS-pt was reproducible across both visit intervals in some (male, NSCLC, low BMI, off chemotherapy), but not all, subgroups. Expressing weight change as categorical variables (WG, WS, WL), did not improve sensitivity to detect a relationship with ΔPS-pt. To examine the consistent correlation between ΔStr Q4 and ΔQoL Q2 more closely, analysis of covariance was performed using the initial QoL Q2 category (good, moderate, poor) as a covariate, and ΔStr Q4 as an explanatory variable in a linear model of ΔQoL Q2. Adding the initial QoL Q2 category as a covariate significantly improved the explanatory power of the model of ΔStr Q4. For the interval between visits 1 and 2, comparing models of linear regression of ΔQoL Q2 vs. ΔStr Q4 (adjusted R 2 =0.09) with ΔQoL Q2 vs. ΔStr Q4 including the initial QoL Q2 category (adjusted R 2 =0.44, P< for comparison of models), confirmed the model including the covariate was significantly better. Similar results were obtained for the second visit interval where the simple linear regression model of Table 4 Correlation matrix for change in weight, and reported performance status, strength and quality of life for two consecutive visit intervals Visit interval ΔPS-pt ΔStr Q4 ΔQoL Q2 Δ% Wt 1 2 R s =0.15* a R s =0.20** R s =0.12* 2 3 R s =0.21* a R s =0.09 R s =0.005 ΔPS-pt 1 2 R s =0.30** R s =0.26** 2 3 R s =0.15 R s =0.10 ΔStr Q4 1 2 R s =0.33** a 2 3 R s =0.38** a Notes: Rs=spearman correlation coefficient; % weight change (Δ% Wt); change in self-reported performance status (ΔPS-pt), change in ratings for feelings of strength (ΔStr Q4 ), and overall quality of life (ΔQoL Q2 ) *P<0.05; **P<0.001 a A significant correlation which was reproducible across two visit intervals

6 2054 Support Care Cancer (2013) 21: ΔQoL Q2 vs. ΔStr Q4 (adjusted R 2 =0.15) was considerably improved by inclusion of the initial QoL Q2 category as a covariate (adjusted R 2 =0.39, P< ). A second independent cohort of patients referred to the CNR-JGH clinic between March 2010 and April 2011 were studied to test the reproducibility of the relationship between Str Q4 and quality of life measured using the FAACT tool. Fifty-six patients were identified for whom complete data on Str Q4 and FAACT scores at both first and second visits was available. These patients were similar to the first cohort in both age (mean (SD): 65.3 (14.7) years) and the proportion of females (26 (46.4 %)) (compare with Table 1). Due to changes in referral patterns the proportion of NSCLC patients was lower, and the three most common cancer types were gastro-intestinal cancers (30.4 %), NSCLC (19.6 %) and haematological malignancies (17.9 %). As before the mean visit interval was 6 weeks, and mean(sd) (5.23(2.54)) and distribution (good/moderate/severe = 25 %/40 %/35 %) of initial Str Q4 scores were almost identical to those recorded in the first cohort (Table 3). Here again, positive correlations were seen between ΔStr Q4 and change in quality of life using FAACT including the total score and all subdomains, except social well-being (Table 5). Discussion Experience in the CNR-JGH clinic suggested that the correlations between changes in objective measures such as weight and other symptoms are not easy to predict from one patient to the next, and even at different points in any one patient s disease trajectory. This is confirmed by the data that shows poor reproducibility of correlations between changes in several of the selected physical symptoms at successive clinic visits (Table 4). Importantly, there was a reproducible positive correlation between weight gain (Δ% Wt) and patient-reported physical functioning (ΔPS-pt) (Table 4). Furthermore, a highly reproducible correlation was identified between changes in perceived strength (ΔStr Q4 ) and a single item quality of life assessment (ΔQoL Q2 ), whatever the patient s reported initial quality of life (Fig. 1). This correlation was replicated when using the multi-domain FAACT tool (Table 5). In our results the Fig. 1 Improvements in feelings of strength correlate with improvements in quality of life (QoL Q2 ) between visits to the CNR-JGH clinic in all categories of initial quality of life. Notes: Each panel shows respective linear regression line with R 2 statistic. *P<0.05; **P< Categories refer to the QoL Q2 scores at first visit for each visit interval: 0 3=good; 4 6=moderate; 7 10=poor change in total FAACT score and scores for all subdomains (with the exception of social well-being) had similar positive correlation with ΔStr Q4. We recognize a number of limitations in interpreting this retrospective study, including the choice of physical function self-report measures (Str Q4 and PS-pt). These were used to investigate the study question as these data were most consistently recorded in the clinical chart for the whole cohort. Despite the relevance of the questions themselves, the psychometric properties of the questions used for strength (Str Q4 ) and quality of life (QoL Q2 ) are uncertain, Table 5 Correlation between change in reported strength and FAACT scores between first and second visits to CNR-JGH clinic ΔTotal% ΔP% ΔF% ΔS% ΔE% ΔAC% ΔStr Q4 (N=56) R s =0.42* R s =0.39* R s =0.33* R s = 0.09 R s =0.29* R s =0.44** Notes: Rs=Spearman correlation coefficient; change in ratings for feelings of strength (ΔStr Q4 ), change in percentage maximum scores of FAACT tool for total (ΔTotal%) and each of the subscales: physical (ΔP%), functional (ΔF%), social (ΔS%), emotional (ΔE%) well-being and anorexia cachexia (ΔAC%) *P<0.05; **P<0.001

7 Support Care Cancer (2013) 21: as to our knowledge these question items have not undergone specific testing, particularly for content and construct validity. However, like our group, many other researchers have modified or altered the question items in the original ESAS tool to include capture of data on symptoms of particular interest[34]; and though some have validated these modified tools, e.g. [35], relatively few have included detailed assessment of validity of individual questions[34, 36]. The questions used in this study were simply for assessing self-reported symptom severity and not for constructing combined scores, but because of uncertainty about the validity of the QoL Q2 question, the FAACT questionnaire is now used for routine clinical assessments in the CNR-JGH clinic. Nevertheless, it is reassuring that the results of the correlation between ΔStr Q4 and ΔQoL Q2 in the first cohort were confirmed in a second independent cohort where change in quality of life was calculated using data from the FAACT tool (Table 5). The correlations we identified were mostly weak (e.g. Δ% WtvsΔPS-pt: R s = ) even though they were both statistically significant and consistent between visits. It should be stressed that we were particularly interested in the correlations between changes in different measures assessed over relatively short time frames between clinic visits (on average 6 7 weeks). Thus the strength of the correlations observed will be influenced by the degree of change in each measure over this time frame. Given the expectation of only modest weight gains or losses over a 6-week interval and the limited sensitivity of PS-pt scale to capture small changes in physical function, the consistent correlation between weight change and change in self-rated performance is likely important and clinically relevant. As the main research question concerned the short-term impact of weight gain on symptoms related to physical functioning, the absence of objective function-related data (e.g. grip strength) is not a critical omission. In addition, though we have attempted to characterize this heterogeneous group of patients as fully as possible, by including data on cancer type, stage, and chemotherapy treatment status, data on many potential confounding factors were not available. Strenuous efforts were made to ensure that patients were weighed without shoes and only wearing light indoor clothing, but it was not possible to reliably correct for other potential sources of variance which might be attributable to use of more than one set of scales in the CNR-JGH clinic over the years covered by this report. Clinically significant changes in hydration status perhaps associated with acute chemotherapy toxicity, or large extracellular fluid shifts causing oedema may also affect measurement of weight; however, the presence of each of these potential confounding events is determined clinically at each visit, and they are unusual in our patients. Body composition analysis, particularly changes in skeletal muscle mass, would give valuable additional information to help interpretation of our results for change in weight and strength; particularly as reduced physical activity will promote loss of muscle and the combined interventions of the CNR-JGH team aim to correct both dietary protein and energy deficits and increase physical activity. However current bedside techniques are not reliable for quantification of total skeletal muscle mass, and these data were not collected routinely in the CNR-JGH clinic. In addition, we realize that chemotherapy, degree of tumour response, other medical complications and psychosocial adjustment to cancer may also impact on reported quality of life and levels of specific symptoms. Finally, this report deals with patients referred to a specialized multi-disciplinary team, that uses a variety of nutritional, physical rehabilitation and symptom management measures to address each patient s problems. As a result we accept that the relationships described may not be generalisable to all patients, or to those seen outside a similar rehabilitation service. Assessing quality of life can be onerous for patients and often requires completion of one of a variety of different, sometimes complex, tools. Furthermore, for the health professionals, deciding how best to intervene to improve quality of life in advanced cancer patients can be challenging. Despite the caveats about the psychometric properties of the QoL Q2 question we used in the current study, mentioned above, the moderately strong and consistent correlation between changes in quality of life and self-reported strength (from Str Q4 ) is noteworthy. Further study is required to define more precisely the patients perception of the Str Q4 question item, in the same way as has recently been attempted for the original ESAS questionnaire [37]. It is possible that perceived strength alone could be used as a simple surrogate for quality of life in cancer cachexia patients, and raises questions about the role of strength or resistance training in improving quality of life in these patients. There is considerable prior data supporting a role for exercise training as an intervention to improve physical function and quality of life in groups of patients with cancer and cancer survivors [22, 38]. However, to date, a special role for resistance training to improve strength and quality of life in cancer patients is supported by some [21], but not all [39] studies. Though the prognostic significance of marked weight loss indicating poor survival in cancer patients is incontrovertible, there is considerable nihilism surrounding the possibility that weight loss in such patients is amenable to any interventions other than the successful deployment of anticancer treatments. There is also matching uncertainty as to whether stabilizing weight or weight gain should be prioritized as a way to actually help improve symptoms, physical function, or indeed survival. In some patients undergoing cancer treatment, dietary interventions alone can make a major contribution to stabilizing weight and quality of life

8 2056 Support Care Cancer (2013) 21: [16, 17]. The current report extends these data to a mixed group of mostly advanced cancer patients, and demonstrates that in the context of a multi-disciplinary team clinic, in which nutritional counseling and interventions are complemented by physical rehabilitation and symptom control, a proportion of patients gain weight, and that weight gain is correlated with improved self-rated performance status. These results support the case for inclusion of combined nutritional and physical rehabilitation interventions in advanced cancer patients with weight loss, as one facet of treatment aimed at optimizing symptom-control and function. Such an approach also addresses the known anxieties expressed by patients and their carers at the frequent failure of health professionals to acknowledge, explain, or act on cancer-related weight loss [40]. Acknowledgements The authors would like to thank Mary Kanbalian for all her help with data collection, supervising data entry and data extraction for this study. In addition, the authors would like to thank the current and past members of the CNR-JGH team for collecting and entering the data used, Dr. Goulnar Kasymjanova for database support during the early years of data collection, and Dr. Neil MacDonald MD and Mary-Ann Dalzell PT who were the founding members of the first CNR-JGH clinic in Finally, the authors gratefully acknowledge Lillian and Stephen Vineberg, and the organizers and participants of the Angel Ball and the Annual Lila Sigal Hockey Marathon for funding to support the CNR-JGH service. Conflict of Interests The authors have no conflict of interests to declare, and also state that individuals or groups who have provided funding for the CNR-JGH activities have not been involved in any aspect of the study design, execution or analysis. 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