Patient-reported outcome measures for physical function in cancer patients: content comparison of the EORTC CAT Core, EORTC QLQ-C30, SF-36, FACT-G, and PROMIS measures using the International Classification of Functioning, Disability and Health

Assessing the performance of QLQ-C30 in predicting all-cause mortality in community cancer patients

BACKGROUND

To evaluate the ability of QLQ-C30 in predicting mortality in community-based cancer patients in China.

METHODS

A whole-cluster sampling method was adopted to enroll cancer patients in four communities in Shanghai from 2018 to 2019. The patients were surveyed using a questionnaire enquiring demographic information, cancer types, and QLQ-C30 scale. Death information of participants was collected and updated from community health care centers. Cox regression models were used to assess the relationship between various QLQ-C30 scores (i.e., total score, five dimension scores, and utility score) and all-cause mortality.

RESULTS

A total of 3,304 participants were enrolled with a mean age of 63.9 years. Among them, 2,710 patients survived while 594 died by 2023. The mean total QLQ-C30 score in living patients was statistically significantly higher than that in deceased patients ( 92.96 vs. 85.21, p < 0.001); and the mean values of the five dimension scores and utility score were also significantly higher for the living patients. Cox regression models with the adjustment of covariates also confirmed that higher QLQ-C30 scores were associated with lower risk of death, with the hazard ratio value being 0.81 for the total score, 0.83-0.89 for the dimension scores, and 0.83 for the utility score, respectively (p < 0.001 for all).

CONCLUSIONS

QLQ-C30 could accurately predict all-cause mortality in Chinese community cancer patients.

Health-related quality of life of individuals dealing with cancer in the Free State: A survey

Background

Cancer is the main cause of morbidity and mortality worldwide, and its symptoms can affect an individual's life holistically.

Objectives

Our study aimed to determine the health-related quality of life (HRQoL) of individuals dealing with cancer in the Free State, South Africa.

Method

A descriptive, cross-sectional study design utilising the standardised Functional Assessment of Cancer Therapy - General (FACT-G) questionnaire as well as a self-developed sociodemographic and general health information questionnaire was used in this study. The study was conducted at the Universitas Annex Oncology Clinic.

Results

A total of 507 participants were conveniently sampled. The median age was 53 years with 73.8% being female. The FACT-G's overall score ranged from 11.7 to 108, with a median of 76.7 (interquartile range [IQR] 63-89.5). The Social or Family Well-Being subscale indicated the highest median of 22.2 and the Emotional Well-Being subscale the lowest of 18. The Physical Well-Being subscale found that 61.8% of individuals felt forced to spend time in bed and 53.4% experienced nausea. The Functional Well-Being subscale showed that 70.3% of individuals accepted their illness and 51.6% enjoyed their life.

Conclusion

Our study highlights the importance of using a clinical assessment tool to determine the influence of cancer on the individual's HRQoL. Involvement of the individual's family and friends during management, as well as identifying the need for psychosocial support, is crucial for positively influencing HRQoL.

Clinical implications

The FACT-G is a valuable tool in guiding physiotherapists and other healthcare professionals with patients' cancer-related treatment experiences.

A Holistic Approach to the Measurement of Physical Function in Clinical Research

Background

This commentary highlights the evolution of our understanding of physical function (PF) and key models/frameworks that have contributed to the current holistic understanding of PF, which encompasses not only a person's performance but also the environment and any adaptations an individual utilizes. This commentary also addresses how digital health tools can facilitate and complement the assessment of holistic PF and enable both objective and subjective input from the participant in their real-world environment. Lastly, we discuss how successful implementation of digital tools within clinical research requires patient input.

Summary

This commentary highlights how our understanding of PF has evolved to be more holistic.

Key Messages

Inclusion of digital tools within clinical research can provide a path forward to holistically assess PF in a patient-focused manner.

The EORTC QLU-C10D distinguished better between cancer patients and the general population than PROPr and EQ-5D-5L in a cross-sectional study

OBJECTIVES

Health state utility (HSU) instruments for calculating quality-adjusted life years, such as the European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Utility - Core 10 Dimensions (QLU-C10D), derived from the EORTC QLQ-30 questionnaire, the Patient-Reported Outcome Measurement Information System (PROMIS) preference score (PROPr), and the EuroQoL-5-Dimensions-5-Levels (EQ-5D-5L), yield different HSU values due to different modeling and different underlying descriptive scales. For example the QLU-C10D includes cancer-relevant dimensions such as nausea. This study aimed to investigate how these differences in descriptive scales contribute to differences in HSU scores by comparing scores of cancer patients receiving chemotherapy to those of the general population.

STUDY DESIGN AND SETTING

EORTC QLU-C10D, PROPr, and EQ-5D-5L scores were obtained for a convenience sample of 484 outpatients of the Department of Oncology, Charité - Universitätsmedizin Berlin, Germany. Convergent and known group's validity were assessed using Pearson's correlation and intraclass correlation coefficients (ICC). We assessed each descriptive dimension score's discriminatory power and compared them to those of the general population (n > 1000) using effect size (ES; Cohen's d) and area under the curve (AUC).

RESULTS

The mean scores of QLU-C10D (0.64; 95% CI 0.62-0.67), PROPr (0.38; 95% CI 0.36-0.40), and EQ-5D-5L (0.72; 95% CI 0.70-0.75) differed significantly, irrespective of sociodemographic factors, condition, or treatment. Conceptually similar descriptive scores as obtained from the HSU instruments showed varying degrees of discrimination in terms of ES and AUC between patients and the general population. The QLU-C10D and its dimensions showed the largest ES and AUC.

CONCLUSION

The QLU-C10D and its domains distinguished best between health states of the two populations, compared to the PROPr and EQ-5D-5L. As the EORTC Core Quality of Life Questionnaire (QLQ-C30) is widely used in clinical practice, its data are available for economic evaluation.

PLAIN LANGUAGE SUMMARY

The assessment of dimensions of health-related quality of life (HRQoL), such as physical functioning or depression, is important to cancer patients and physicians for treatment and side effect monitoring. Descriptive HRQoL is measured by patient-reported outcomes measures (PROM). The European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30 questionnaire and the Patient-Reported Outcome Measurement Information System (PROMIS) are the most common PROM in the clinical HRQoL assessment. In recent years, multidimensional preference-based HRQoL measures were developed using these PROM as dimensions. These preference-based measures, also referred to as health state utility (HSU) scores, are needed for economic evaluations of treatments. The QLQ-C30's corresponding HSU score is the Quality of Life Utility measure-Core 10 Dimensions (QLU-C10D), and PROMIS' HSU score is the PROMIS preference score (PROPr). Both new HSU scores are frequently compared to the well-established EuroQoL-5-dimensions-5-levels (EQ-5D-5L). They all conceptualize HSU differently, as they assess different dimensions of HRQoL und use different models. Both the QLU-C10D and the PROPr have thus shown systematic differences to the EQ-5D-5L but these were largely consistent across the subgroups. Convergent and known groups validity can therefore be considered established. However, as HSU is a multidimensional construct, it remains unclear how differences in its dimensions, for example, its descriptive scales, contribute to differences in HSU scores. This is of importance as it is the descriptive scales that measure clinical HRQoL. We investigated this question by assessing each dimension's ability to distinguish between a sample of 484 cancer patients and the German general population. We could show that the ability to distinguish depended on the domain: for example, for depression, the QLU-C10D and EQ-5D-5L distinguished clearer, while for physical function, PROMIS did. Overall, the QLU-C10D and its dimensions distinguish best between cancer patients and general population.

Comparing the contents of patient-reported outcome measures for fatigue: EORTC CAT Core, EORTC QLQ-C30, EORTC QLQ-FA12, FACIT, PRO-CTCAE, PROMIS, Brief Fatigue Inventory, Multidimensional Fatigue Inventory, and Piper Fatigue Scale

BACKGROUND

To assess fatigue in cancer patients, several patient-reported outcome measures (PROMs) are available that differ in content. To support the selection of suitable measures for specific applications and to evaluate possibilities of quantitative linking, the present study provides a content comparison of common fatigue measures, scales, and item banks. We included the EORTC CAT Core, EORTC QLQ-FA12, EORTC QLQ-C30, FACIT-F, PROMIS Fatigue (Cancer item bank v1.0), Brief Fatigue Inventory (BFI), Multidimensional Fatigue Inventory (MFI-20), Piper Fatigue Scale (PFS-12), and PRO-CTCAE.

METHODS

All items of the included measures were linked to the International Classification of Functioning, Disability and Health (ICF). Additionally, they were categorized as assessing general, physical, emotional, or cognitive fatigue. Descriptive statistics were used to display the contents covered in each measure and to allow for a qualitative comparison.

RESULTS

The measures consist of 160 items in total and covered primarily contents of the ICF components 'Body functions', 'Activities and participation', and 'Environmental Factors'. Most ICF codings refer to 'b1300 Energy level' (9-67% of the codings per instrument; 47% of all coded content). Within the broad categorization of types of fatigue, most items were classified as general fatigue (33-100% of the codings per instrument; 49% of the overall item pool). While the EORTC CAT Core focuses exclusively on physical and general fatigue, FACIT and BFI additionally assess emotional fatigue. The EORTC QLQ-FA12, PROMIS, MFI-20, and PFS-12 cover all fatigue components, including cognitive fatigue.

DISCUSSION

The review provides an in-depth content comparison of PROMs assessing cancer-related fatigue. This can inform the selection of suitable measures in different clinical contexts. Furthermore, it will inform quantitative analyses to facilitate comparison of scores obtained with different PROMs.

The PROPr can be measured using different PROMIS domain item sets

BACKGROUND

The Patient-Reported Outcomes Measurement Information System (PROMIS) Preference Score (PROPr) is estimated from descriptive health assessments within the PROMIS framework. The underlying item response theory (IRT) allows researchers to measure PROMIS health domains with any subset of items that are calibrated to this domain. Consequently, this should also be true for the PROPr. We aimed to test this assumption using both an empirical and a simulation approach.

METHODS

Empirically, we estimated 3 PROMIS Pain inference (PI) scores from 3 different item subsets in a sample of n=199 cancer patients: 4 PROMIS-29 items (estimate: θ4), the 2 original PROPr items (θ2), and 10 different items (θ10). We calculated mean differences and agreement between θ4, and θ2 and θ10, respectively, and between their resulting PROPr4, PROPr2, PROPr10, using intraclass correlation coefficients (ICC) and Bland-Altman (B-A) plots with 95 %-Limits of Agreement (LoA). For the simulation, we used the IRT-model to calculate all item responses of the entire 7 PROPr domain item banks from the empirically observed PROMIS-29+cognition θ. From these simulated item banks, we chose the 2 original PROPr items per domain to calculate PROPrsim and compared it to PROPr4 again using ICC and B-A plots.

RESULTS

θ4 vs θ10 showed smaller bias (-0.012, 95 %-LoA -0.88;0.85) than θ4 vs θ2 (0.025, 95 %-LoA -0.95;1.00. ICC>0.85 (p<0.001) in both θ-comparisons. PROPr4 vs PROPr10 showed lower bias (0.0012, 95 %-LoA -0.039;0.042) than PROPr4 vs PROPr2 (-0.0029, 95 %-LoA -0.049;0.044). ICC>0.98 (p<0.0001) on both PROPr-comparisons. Mean PROPrsim was larger than mean PROPr4 (0.0228, 95 %-LoA -0.1103; 0.1558) and ICC was 0.95 (95 %CI 0.93; 0.97).

CONCLUSION

Different item subsets can be used to estimate the PROMIS PI for calculation of the PROPr. Reduction to 2 items per domain rather than 4 does not significantly change the PROPr estimate on average. Agreements differ across the spectrum and in individual comparisons.

Non-pharmacological interventions targeting mobility among people with advanced cancer: a systematic review

PURPOSE

To synthesise evidence evaluating non-pharmacological interventions targeting mobility among people with advanced cancer, considering the type, efficacy and contextual factors that may influence outcome.

METHODS

Systematic review of studies of non-pharmacological interventions in adults (≥ 18 years) with advanced (stage III-IV) cancer, and assessing mobility using clinical or patient-reported outcome measures. Searches were conducted across three electronic databases (MEDLINE, EMBASE and CINAHL) up to June 2024. Methodological quality was assessed using Joanna Briggs Institute tools and contextual factors were evaluated through the Context and Implementation of Complex Interventions framework. A narrative synthesis was conducted due to clinical heterogeneity of included studies.

RESULTS

38 studies encompassing 2,464 participants were included. The most frequent mobility outcome measure was the 6-min walk test (26/38 studies). Exercise was the most common intervention, (33 studies: 27 aerobic and resistance, 5 aerobic, 1 resistance versus aerobic training) and improvements in mobility were found in 21/33 outcomes. Electrotherapy interventions led to significant improvements in mobility in 3/5 studies. Geographical factors (e.g. distance, transport, parking requirements) potentially limited participation in 18/38 studies. A lack of ethnic diversity among populations was evident and language proficiency was an inclusion criterion in 12 studies.

CONCLUSION

Exercise and neuromuscular electrical stimulation appear to improve mobility outcomes in advanced cancer. The evaluation of other non-pharmacological interventions targeting mobility should consider access and inclusivity, and be adaptable to the needs of this population.

Facets of physical function assessed by patient-reported outcome measures in oncology research

PURPOSE

The U.S. Food & Drug Administration has identified physical functioning (PF) as a core patient-reported outcome (PRO) in cancer clinical trials. The purpose of this study was to identify PF PRO measures (PROMs) in adult cancer populations and classify the PROMs by content covered (facets of PF) in each measure.

METHODS

As part of the Patient Reports of Physical Functioning Study (PROPS) research program, we conducted a targeted literature review to identify PROMs that could be used in clinical trials to evaluate PF from the patient perspective. Next, we convened an advisory panel to conduct a modified, reactive, Delphi study to reach consensus on which PF facets are assessed by PROMs identified in the review. The panel engaged in a "card sort" activity to classify PROM items by PF facets. Consensus was reached when 80% of panel members agreed that at least one facet was being measured by each PROM item.

RESULTS

The literature review identified 13 PROMs that met inclusion criteria. Eight facets of PF were identified for classification in the Delphi study: ability, completion, difficulty, limitation, quality, frequency, bother, and satisfaction. Through two rounds, the panel documented and classified conceptual approaches for each PRO item presented. The most prevalent PF facets were ability, difficulty, and limitation.

CONCLUSION

Classifying PF PROMs by PF facets will promote more consistent communication regarding the aspects of PF represented in each PROM, helping researchers prioritize measures for inclusion in cancer clinical trials.

The TEOGIC study project: a comprehensive characterization of early onset gastrointestinal cancer in the Northern area of Spain

BACKGROUND

Gastrointestinal cancers represent one of the most prevalent diseases worldwide. Strikingly, the incidence of Early Onset Gastrointestinal Cancer (EOGIC) has been rising during the last decades and changes in lifestyle and environmental exposure seem to play a role. EOGIC has been defined as a different entity compared to on-average gastrointestinal cancer, with distinct clinical and molecular characteristics. Inherent to the particularities of younger age, there is an unmet need for a tailored approach for the management of these patients. The TEOGIC proposes a comprehensive study to characterize EOGIC patients in the northern of Spain.

METHODS

Patients with histologically confirmed new diagnosis of colorectal, gastroesophageal and pancreatic adenocarcinoma will be considered for two cohorts: EOGIC (≤ 50 years old) and non-EOGIC (60-75 years old), with a ratio of 1:2. Two hundred and forty patients will be recruited in 4 Public Hospitals from northern Spain. After receiving unified informed consent, demographic and clinical data of the patients will be collected in a REDCap database. Lifestyle related data will be obtained in questionnaires assessing diet, physical activity and the general quality of life of the patients before diagnosis. Biological samples prior to any onco-specific treatment will be obtained for the analyses of circulating inflammatory proteins, gut microbiota, and the proteome of the tumor microenvironment. Histologic characteristics and routine biomarkers will be also collected. Thereafter, data will be integrated and analyzed to assess tumor specific, pan-tumor and sex-associated differential characteristics of EOGIC.

DISCUSSION

The underlying risk factors and differential characteristics of EOGIC remain poorly studied, particularly in our geographical area. Although limited by the exploratory nature and the small sample size estimated to be recruited, TEOGIC represents the first attempt to comprehensively characterize these young patients, and thus attend to their special needs. Findings derived from this study could contribute to raise awareness and preventive behaviors in the population. In parallel, molecular studies could lead to the identification of potential novel non-invasive biomarkers and therapeutic targets that would help in the development of the tailored clinical management of these patients, focusing on screening programs for early diagnosis and precision medicine.

Evaluating the effect of a mobile-based symptom monitoring system for improving physical function in patients with cancer during chemotherapy: study protocol for a multicentre randomised controlled trial

INTRODUCTION

Symptoms due to chemotherapy are common in patients with cancer. Cancer-related symptoms are closely associated with the deterioration of physical function which can be associated with decreased quality of life and increased mortality. Thus, timely symptom identification is critical for improving cancer prognosis and survival. Recently, remote symptom monitoring system using digital technology has demonstrated its effects on symptom control or survival. However, few studies examined whether remote monitoring would contribute to retaining physical function among patients with cancer. Therefore, this study aimed to evaluate the effectiveness of mobile-based symptom monitoring in improving physical function among patients with cancer under chemotherapy.

METHODS AND ANALYSIS

This study is a multicentre, open-label, parallel-group, randomised controlled trial. We will recruit 372 patients at three tertiary hospitals located in Seoul, South Korea. Study participants will be randomly assigned to either an intervention group receiving the ePRO-CTCAE app and a control group receiving routine clinical practice only. The primary outcome is changes in physical function from commencement to completion of planned chemotherapy. A linear mixed model will be performed under the intention-to-treat principle. The secondary outcomes include physical activity level; changes in pain interference; changes in depressive symptom; unplanned clinical visits; additional medical expenditure for symptom management; completion rate of planned chemotherapy; changes in symptom burden and health-related quality of life; and 1-year overall mortality.

ETHICS AND DISSEMINATION

The study has been approved by the institutional review board and ethics committee at the three university hospitals involved in this trial. Written informed consent will be obtained from all the participants. The results of the trial will be submitted for publication in peer-reviewed academic journals and disseminated through relevant literatures.

TRIAL REGISTRATION NUMBER

KCT0007220.

Development of a Conversion Table Linking Functional Independence Measure Scores to International Classification of Functioning, Disability, and Health Qualifiers: Insights from a Survey of Healthcare Professionals

In clinical practice, patient assessments rely on established scales. Integrating data from these scales into the International Classification of Functioning, Disability, and Health (ICF) framework has been suggested; however, a standardized approach is lacking. Herein, we tested a new approach to develop a conversion table translating clinical scale scores into ICF qualifiers based on a clinician survey. The survey queried rehabilitation professionals about which functional independence measure (FIM) item scores (1-7) corresponded to the ICF qualifiers (0-4). A total of 458 rehabilitation professionals participated. The survey findings indicated a general consensus on the equivalence of FIM scores with ICF qualifiers. The median value for each item remained consistent across all item groups. Specifically, FIM 1 had a median value of 4; FIM 2 and 3 both had median values of 3; FIM 4 and 5 both had median values of 2; FIM 6 had a median value of 1; and FIM 7 had a median value of 0. Despite limitations due to the irreconcilable differences between the frameworks of existing scales and the ICF, these results underline the ICF's potential to serve as a central hub for integrating clinical data from various scales.

Unmet Needs, Quality of Life, and Financial Toxicity Among Survivors of Lung Cancer

Importance

Despite a growing population of survivors of lung cancer, there is limited understanding of the survivorship journey. Survivors of lung cancer experience unmet physical, social, emotional, and medical needs regardless of stage at diagnosis or treatment modalities.

Objective

To investigate the association of unmet needs with quality of life (QOL) and financial toxicity (FT) among survivors of lung cancer.

Design, Setting, and Participants

This survey study was conducted at Johns Hopkins Sidney Kimmel Comprehensive Cancer Center thoracic oncology clinics between December 1, 2020, and September 30, 2021, to assess needs (physical, social, emotional, and medical), QOL, and FT among survivors of lung cancer. Patients had non-small cell lung cancer of any stage and were alive longer than 1 year from diagnosis. A cross-sectional survey was administered, which consisted of an adapted needs survey developed by the Mayo Survey Research Center, the Comprehensive Score for Financial Toxicity measure, and the European Organization for Research and Treatment of Cancer QLQ-C30 QOL scale. Demographic and clinical information was obtained through retrospective medical record review. Data analysis was performed between May 9 and December 8, 2022.

Main Outcomes and Measures

Separate multiple linear regression models, treating QOL and FT as dependent variables, were performed to assess the adjusted association of total number of unmet needs and type of unmet need (physical, emotional, social, or medical) with QOL and FT.

Results

Of the 360 survivors of lung cancer approached, 232 completed the survey and were included in this study. These 232 respondents had a median age of 69 (IQR, 60.5-75.0) years. Most respondents were women (144 [62.1%]), were married (165 [71.1%]), and had stage III or IV lung cancer (140 [60.3%]). Race and ethnicity was reported as Black (33 [14.2%]), White (172 [74.1%]), or other race or ethnicity (27 [11.6%]). A higher number of total unmet needs was associated with lower QOL (β [SE], -1.37 [0.18]; P < .001) and higher FT (β [SE], -0.33 [0.45]; P < .001). In the context of needs domains, greater unmet physical needs (β [SE], -1.24 [0.54]; P = .02), social needs (β [SE], -3.60 [1.34]; P = .01), and medical needs (β [SE], -2.66 [0.98]; P = .01) were associated with lower QOL, whereas only greater social needs was associated with higher FT (β [SE], -3.40 [0.53]; P < .001).

Conclusions and Relevance

The findings of this survey study suggest that among survivors of lung cancer, unmet needs were associated with lower QOL and higher FT. Future studies evaluating targeted interventions to address these unmet needs may improve QOL and FT among survivors of lung cancer.

"The Ability to Go Out into the World Is the Most Important Thing"-A Qualitative Study of Important Exercise Outcomes for People with Lung Cancer

Whilst existing quantitative research identifies outcomes believed to be important by researchers and clinicians, it may neglect outcomes that are meaningful to patients. This study aimed to explore the outcomes of exercise that are important to people with lung cancer and their carers. Data collection involved a qualitative methodology including semi-structured interviews and focus groups. Question guide development was informed by the International Classification of Functioning (ICF) framework. Data were analyzed by two researchers with NVivo (v12) software using a conventional content analysis process, followed by directed content analysis to map outcomes to the ICF. Conduct and reporting adhered to COREQ guidelines. Fifteen participants provided data. Most participants had received their diagnoses 24 months prior to study involvement (n = 9), and one-third had completed treatment (n = 5). Important outcomes were reported by participants across all domains of the ICF: activity and participation (n = 24), body function (n = 19), body structure (n = 5), environmental factors (n = 5), and personal factors (n = 1). Additional code categories pertained to the impacts of non-cancer factors such as age, frailty, and comorbidities; identifying barriers to exercise; and individualizing outcome measures. Clinicians and researchers should consider selecting outcomes from all relevant domains of the ICF, with a focus on the activity and participation domain, in addition to non-cancer factors such as ageing, frailty, and co-morbidities. Feedback should be provided to patients following outcome measures collection and reassessment.

Equipercentile equating of scores from common patient-reported outcome measures of physical function in patients with cancer

OBJECTIVE

To provide equipercentile equating of physical function (PF) scores from frequently used patient-reported outcome measures (PROMs) in cancer patients to facilitate data pooling and comparisons.

STUDY DESIGN AND SETTING

Adult cancer patients from five European countries completed the European Organization for Research and Treatment of Cancer (EORTC) computer adaptive test (CAT) Core, EORTC Quality of Life Questionnaire Version 3.0 (QLQ-C30), Functional Assessment of Cancer Therapy - General (FACT-G), 36-item Short Form Health Survey (SF-36), and the Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function 20a short form. The R package "equate" was used to establish conversion tables of PF scores on those measures with a bivariate rank correlation of at least 0.75.

RESULTS

In total, 953 patients with cancer (mean age 58.9 years, 54.7% men) participated. Bivariate rank correlations between PF scores from the EORTC CAT Core, EORTC QLQ-C30, SF-36, and PROMIS were all above 0.85, but below 0.69 for the FACT-G. Conversion tables were established for all measures but the FACT-G. These tables indicate which score from one PROM best matches the score from another PROM and provide standard errors of converted scores.

CONCLUSION

Our analysis indicates that linking of PF scores from both EORTC measures (CAT and QLQ-C30) with PROMIS and SF-36 is possible, whereas the physical domain of the FACT-G seems to be different. The established conversion tables may be used for comparing results or pooling data from clinical studies using different PROMs.

Establishing a common metric for physical function: Linking SARC-F and PROMIS® physical function

INTRODUCTION

Aligned with the increasing need for standardized assessment of physical function in older individuals with cancer and other conditions, several patient-reported outcome measures (PROMs) have been developed and published. The aim of this study is to link the Strength, Assistance with walking, Rising from a chair, Climbing stairs, and Falls questionnaire (SARC-F), and the Patient-Reported Outcomes Measurement Information System® (PROMIS®) Physical Function Short Form 8c (PROMIS PF 8c), and make their scores convertible, in order to expand the use of both instruments in research and inform clinicians and researchers about the interchangeability of critical cut-off scores.

MATERIALS AND METHODS

The sample included 300 participants recruited from an online panel. Participants were included if they had received a cancer diagnosis from a clinician and reported receiving anti-cancer treatment. We conducted five linking procedures and selected an optimal one to generate the crosswalk table between the two measures.

RESULTS

The linked T scores of all five methods showed acceptably small mean differences from the observed T scores, and the standard deviation (SD), and root-mean-squared deviation (RMSD) of the differences were generally similar across all methods. After comparing across all statistics, the Stocking-Lord approach was considered as the optimal approach to compute the crosswalk table for converting SARC-F raw scores to PROMIS PF 8c scores. The crosswalk table shows that the SARC-F cut-off value of 4 between healthy versus symptomatic with a corresponding score of 37 fell in the range of moderate physical function limitation from 30 to 39 on the PROMI PF 8c T score metric.

DISCUSSION

The linkage in this study has potential for improving clinical and research activities for people with cancer and perhaps others with a similar range of physical function. It facilitates the interpretability in scores of both measures on a common metric anchored on general population for further group-level analysis. Researchers can use this crosswalk to harmonize data collected from either instrument without requiring all cohorts to administer the same instrument for a prospective data collection or retrospective data analysis purpose or for a cross-study effectiveness study.

Physical function endpoints in cancer cachexia clinical trials: Systematic Review 1 of the cachexia endpoints series

In cancer cachexia trials, measures of physical function are commonly used as endpoints. For drug trials to obtain regulatory approval, efficacy in physical function endpoints may be needed alongside other measures. However, it is not clear which physical function endpoints should be used. The aim of this systematic review was to assess the frequency and diversity of physical function endpoints in cancer cachexia trials. Following a comprehensive electronic literature search of MEDLINE, Embase and Cochrane (1990-2021), records were retrieved. Eligible trials met the following criteria: adults (≥18 years), controlled design, more than 40 participants, use of a cachexia intervention for more than 14 days and use of a physical function endpoint. Physical function measures were classified as an objective measure (hand grip strength [HGS], stair climb power [SCP], timed up and go [TUG] test, 6-min walking test [6MWT] and short physical performance battery [SPPB]), clinician assessment of function (Karnofsky Performance Status [KPS] or Eastern Cooperative Oncology Group-Performance Status [ECOG-PS]) or patient-reported outcomes (physical function subscale of the European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaires [EORTC QLQ-C30 or C15]). Data extraction was performed using Covidence and followed PRISMA guidance (PROSPERO registration: CRD42022276710). A total of 5975 potential studies were examined and 71 were eligible. Pharmacological interventions were assessed in 38 trials (54%). Of these, 11 (29%, n = 1184) examined megestrol and 5 (13%, n = 1928) examined anamorelin; nutritional interventions were assessed in 21 trials (30%); and exercise-based interventions were assessed in 6 trials (8%). The remaining six trials (8%) assessed multimodal interventions. Among the objective measures of physical function (assessed as primary or secondary endpoints), HGS was most commonly examined (33 trials, n = 5081) and demonstrated a statistically significant finding in 12 (36%) trials (n = 2091). The 6MWT was assessed in 12 trials (n = 1074) and was statistically significant in 4 (33%) trials (n = 403), whereas SCP, TUG and SPPB were each assessed in 3 trials. KPS was more commonly assessed than the newer ECOG-PS (16 vs. 9 trials), and patient-reported EORTC QLQ-C30 physical function was reported in 25 trials. HGS is the most commonly used physical function endpoint in cancer cachexia clinical trials. However, heterogeneity in study design, populations, intervention and endpoint selection make it difficult to comment on the optimal endpoint and how to measure this. We offer several recommendations/considerations to improve the design of future clinical trials in cancer cachexia.