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. 2025 Sep 11;11(11):1303–1312. doi: 10.1001/jamaoncol.2025.3153

Patient-Reported Outcomes as Prognostic Indicators for Overall Survival in Cancer

A Systematic Review and Meta-Analysis

Ryan S Huang 1, David Chen 1, Ali Benour 1, Ryan Cortez 1, Andrew Mihalache 1, Carlton Johnny 1,2, Andrea Bezjak 1,2, Robert A Olson 3,4, Srinivas Raman 3,4,✉
PMCID: PMC12426862  PMID: 40932728

Key Points

Question

Do patient-reported outcomes contain independent prognostic information about overall survival for patients with cancer?

Findings

In this systematic review and meta-analysis of 69 randomized clinical trials that included 44 030 patients with cancer, higher baseline global health status, physical functioning, and role functioning scores were significantly associated with improved overall survival, while greater symptom burden, including nausea and vomiting, pain, fatigue, appetite loss, and dyspnea, was associated with worse overall survival.

Meaning

The study results suggest that patient-reported outcomes capture clinically relevant prognostic information beyond traditional clinical end points and may enhance risk stratification and personalized treatment approaches in oncology.

Abstract

Importance

Patient-reported outcomes (PROs) are health data that are collected directly from patients to assess symptoms, functional status, and quality of life. While studies have reported associations between PROs and survival, the prognostic significance of specific PRO domains has not been systematically quantified.

Objective

To evaluate the association between baseline PROs and overall survival (OS) in patients with cancer and quantify the prognostic significance of various PRO domains through a systematic review and meta-analysis of randomized clinical trials (RCTs).

Data Sources

A systematic literature search of PubMed (MEDLINE), Ovid Embase, and the Cochrane Library was conducted to identify eligible studies published between January 1, 2000, and June 1, 2024. The data were analyzed on January 15, 2025.

Study Selection

Eligible studies were prospective RCTs that enrolled adult patients with cancer (18 years or older) that included at least 1 baseline PRO measure, reported OS as an outcome, and conducted multivariate analyses that adjusted for clinical and disease-related confounders.

Data Extraction and Synthesis

Data from eligible RCTs were extracted independently and in duplicate by 4 reviewers. Studies using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire were meta-analyzed using a random-effects model with an inverse variance–weighted approach.

Main Outcome and Measure

The primary outcome was the association between baseline PROs and OS reported using pooled hazard ratios (HRs) and 95% CIs.

Results

A total of 69 RCTs comprising 44 030 patients were included in the systematic review, with 31 RCTs (44.9%) meeting criteria for the meta-analysis. Higher global health status scores and quality of life were associated with improved OS (hazard ratio [HR], 0.99; 95% CI, 0.98-0.99). Among functional scales, physical functioning (HR, 0.94; 95% CI, 0.92-0.96) and role functioning (HR, 0.96; 95% CI, 0.94-0.98) were associated with improved OS. Conversely, higher symptom burden, including nausea and vomiting (HR, 1.12; 95% CI, 1.04-1.21), fatigue (HR, 1.05; 95% CI, 1.00-1.10), and pain (HR, 1.07; 95% CI, 1.04-1.11), was associated with worse OS. The overall pooled effect demonstrated that increasing individual symptom severity was associated with higher mortality risk (HR, 1.03; 95% CI, 1.01-1.04). The Egger test showed no evidence of publication bias.

Conclusions and Relevance

This systematic review and meta-analysis found that PROs offer independent prognostic information for cancer survival. These findings support the integration of PRO assessments into clinical decision-making and risk stratification in oncology.

This systematic review and meta-analysis evaluates the association between baseline patient-reported outcomes and overall survival in patients with cancer.

Introduction

Patient-reported outcomes (PROs) have become essential tools in cancer research and clinical practice, providing critical insights into patients’ subjective experiences throughout their treatment journey.1 While traditionally used to assess treatment-related toxic effects and quality of life, emerging evidence suggests that PROs may also serve as valuable prognostic indicators for clinical outcomes.2

Conventional prognostic factors, such as disease stage, performance status, and biomarkers, have primarily guided treatment decisions and outcome predictions. However, these clinical parameters may not fully account for the complex interplay between a patient’s physical condition, psychological state, and social functioning, all of which may be associated with disease progression and survival. Previous reviews identified significant associations between baseline PRO measures and survival in patients with cancer.3,4 Despite these promising findings, the integration of PROs into clinical decision-making remains limited, partially due to uncertainties regarding which specific PRO domains are most relevant across different cancer populations. Additionally, prior reviews have varied in their methods, with some including nonrandomized study designs, heterogeneous patient populations, and a lack of comprehensive statistical summarization.3,4,5,6 To address these limitations, this study aimed to systematically review randomized clinical trials (RCTs) that evaluated the prognostic value of PROs in cancer survival. Furthermore, it aimed to meta-analyze data from studies using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30), the most commonly used PRO instrument, to quantify the prognostic significance of various PRO domains.

Methods

This study was registered in the International Prospective Register of Systematic Reviews (CRD42024563125). It adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines and was conducted according to the Declaration of Helsinki.7 Research ethics board approval and participant consent was not required for this study due to its design. No cancer survivors or patient representatives were involved in any aspect of the study.

Search Strategy and Eligibility Criteria

We conducted a systematic literature search of PubMed (MEDLINE), Ovid Embase, and the Cochrane Library from January 1, 2000, to June 1, 2024, to identify relevant RCTs that evaluated the prognostic value of PROs in predicting overall survival (OS) for patients with cancer. The full search strategy is provided in eTable 1 in Supplement 1. Studies were eligible for inclusion if they met the following criteria: (1) enrolled adult patients (18 years or older) from prospective phase 2, 3, or 4 RCTs that evaluated cancer treatment; (2) included at least 1 PRO measure, defined as a patient-reported indicator of well-being; (3) provided data on OS; and (4) performed at least 1 multivariate analysis that assessed the association between baseline PROs and OS while controlling for clinical and disease-related factors. The exclusion criteria were as follows: (1) nonrandomized studies, including case reports, case series, cohort studies, and case-control studies; (2) studies that focused solely on the framework, feasibility, or cost of PRO integration rather than survival outcomes; and (3) studies that used proxy-reported outcomes instead of direct PRO assessments. Additionally, we excluded conference abstracts, preprint articles, editorials, systematic reviews, meta-analyses, letters to the editor, or studies with fewer than 10 participants.

For inclusion in the meta-analysis portion of this investigation, additional criteria were applied. Studies were required to have reported a hazard ratio (HR) from a multivariate analysis that assessed 1 or more components of the EORTC QLQ-C30 as a prognostic indicator of OS. The EORTC QLQ-C30 is a widely validated and extensively used PRO instrument in oncology that was designed to assess multiple dimensions of health-related quality of life in patients with cancer.8,9 It contains 5 functioning scales (physical, role, emotional, cognitive, and social), 3 symptom scales (fatigue, pain, nausea/vomiting), the global health status/quality of life (GHQ) scale, and an assessment of additional single items, including appetite loss, insomnia, constipation, and diarrhea.9 For inclusion in the meta-analysis, PRO scales were required to have been reported as continuous variables rather than categorical or dichotomized measures to ensure methodological consistency and facilitate appropriate pooling of effect estimates. Studies that used other PRO instruments or dichotomized EORTC QLQ-C30 scores or those that reported HRs in a format that was unsuitable for pooled analysis were included in the systematic review but excluded from the meta-analysis. To mitigate redundancy, only the most recent and relevant publication was included for overlapping cohorts, with data extracted from published sources.

Study Selection and Data Collection

The initial review of titles and abstracts was conducted independently and in duplicate by 4 reviewers (D.C., A.B., R.C., and C.J.). This stage incorporated a calibration phase in which both reviewers jointly screened a subset of articles to ensure uniform application of the inclusion criteria. Full texts were then independently evaluated by the same reviewers. Disagreements were resolved through discussion, and if consensus could not be reached, a fifth independent reviewer (S.R.) provided the final decision. All screening was conducted using Covidence (Veritas Health Innovation) and all data were collected on Microsoft Excel. We extracted the following information from each eligible study: publication year, clinical trial phase, cancer type and classification, sample size, PRO instruments used, PRO domains significantly associated with survival outcomes, and significant confounding variables included in multivariate analyses. Two independent reviewers (A.B. and R.C.) independently evaluated the risk of bias in the included RCTs using the Cochrane Risk of Bias 2 assessment tool.10 In cases of disagreement, a third independent reviewer (S.R.) was consulted to resolve the discrepancies.

Statistical Analysis

The study characteristics and demographic profiles of included participants were summarized using descriptive statistics. In the systematic review component, we comprehensively synthesized all PRO measures that demonstrated statistically significant associations with OS across the included studies. For the quantitative meta-analysis, we assessed the prognostic value of specific PRO domains on OS by pooling HRs from studies that used the EORTC QLQ-C30 instrument. Pooled HRs with corresponding 95% CIs were calculated using a random-effects meta-analysis with the inverse variance–weighting method to account for between-study heterogeneity. Heterogeneity across the studies was assessed using the I2 statistic. Subgroup analyses were conducted for each domain of the EORTC QLQ-C30 instrument when at least 2 studies reported outcomes using the same scale. Additionally, we performed stratified analyses by scale type (ie, functional, symptom, and single-item scales) to identify patterns in prognostic significance across different aspects of patient-reported health status. Publication bias was assessed using funnel plots for visual inspection of asymmetry and formally evaluated with the Egger regression test.11 Statistical significance was set at 2-tailed P > .05 across all analyses. All statistical procedures were performed using StataBE, version 18.0 (StataCorp).

Results

Following the screening of the titles and abstracts of 5502 studies, 265 full-text articles were assessed for eligibility, resulting in the inclusion of 44 030 patients across 69 RCTs in the systematic review (eFigure 1 in Supplement 1). Most trials were phase 3 (58 [84%]), with fewer being phase 2 (4 [6%]) or mixed-phase studies (7 [10%]). Studies were conducted across multiple countries, with the highest representation based on corresponding author location from the US (22 [32%]), followed by France (11 [16%]) and Belgium (9 [13%]). The most commonly studied cancer types were lung cancer (14 [20%]),12,13,14,15,16,17,18,19,20,21,22,23,24,25 followed by head and neck cancer (8 [12%]),24,26,27,28,29,30,31,32 pancreatic cancer (8 [12%]),24,33,34,35,36,37,38,39 colorectal cancer (7 [10%]),24,40,41,42,43,44,45 and prostate cancer (7 [10%]).24,46,47,48,49,50,51 A detailed breakdown by cancer type is provided in the Table. The EORTC QLQ scales were the most frequently used PRO instrument (39 studies [57%]),12,13,16,18,21,22,23,24,28,35,36,37,38,40,42,43,45,49,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72 followed by the Functional Assessment of Cancer Therapy (FACT) scales (14 studies [20%]).15,17,19,20,26,27,29,30,48,62,73,74,75,76 Other PRO instruments used included the EuroQol 5-Dimension scale that was used in 4 studies,30,34,41,44 the Brief Pain Inventory that was used in 4 studies,46,51,73,77 and the following scales that were used in 2 studies each: Lung Cancer Symptom Scale,14,15 Head and Neck Radiotherapy Questionnaire,28,31 Perceived Stress Scale,30,31 Rotterdam Symptom Checklist,77,78 and Spitzer Quality of Life Index.31,79 Six studies used trial-specific scales.25,32,33,39,47,50 Among the 69 RCTs included in the systematic review, 65 studies (94%) found at least 1 PRO measure to be significantly associated with OS in multivariable analyses. Physical functioning emerged as the most consistent prognostic factor, reported to be significantly associated with OS in 27 studies (39%). A complete summary of significant PRO prognostic factors for OS and other significant variables identified on multivariable analysis in each study is summarized in eTable 2 in Supplement 1.

Table. Characteristics of Included Randomized Clinical Trials.

Category No. of studies (%) (N = 69)
Trial phase
3 58 (84.1)
2 4 (5.8)
Mixed 7 (10.1)
Country
US 22 (31.9)
France 11 (15.9)
Belgium 9 (13.0)
Australia 6 (8.7)
Canada 3 (4.3)
Italy 3 (4.3)
Netherlands 3 (4.3)
Sweden 3 (4.3)
UK 3 (4.3)
Germany 2 (2.9)
Switzerland 2 (2.9)
Japan 1 (1.4)
Korea 1 (1.4)
Cancer type
Lung 14 (20.3)
Head and neck 8 (11.6)
Pancreatic 8 (11.6)
Prostate 7 (10.1)
Colorectal 7 (10.1)
Esophageal 6 (8.7)
Breast 6 (8.7)
Ovarian 6 (8.7)
Brain 5 (7.2)
Gastric 4 (5.8)
Hepatocellular carcinoma 2 (2.9)
Bladder 2 (2.9)
Melanoma 2 (2.9)
Testicular 1 (1.4)
Patient-reported outcome measures
EORTC Quality of Life scales 39 (56.5)
Functional assessment of cancer therapy 14 (20.3)
EuroQol 5-Dimension 4 (5.8)
Brief pain inventory 4 (5.8)
Lung Cancer Symptom scale 2 (2.9)
Head and Neck Radiotherapy Questionnaire 2 (2.9)
Perceived Stress scale 2 (2.9)
Rotterdam symptom checklist 2 (2.9)
Spitzer Quality of Life Index 2 (2.9)
Other trial specific scales 6 (8.7)
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Abbreviation: EORTC, European Organization for Research and Treatment of Cancer.

Thirty-one studies met the inclusion criteria and were included in the meta-analysis.12,13,16,18,21,22,24,28,35,36,37,38,40,45,49,52,53,54,56,57,59,61,62,63,64,65,66,67,69,70,71 A summary of PROs that were included as covariates in multivariable models across studies included in the meta-analysis is provided in eTable 3 in Supplement 1. Higher scores on the GHQ scale were associated with improved OS (HR, 0.99; 95% CI, 0.98-0.99; I2 = 60%; Figure 1). Among functional scales, physical functioning (HR, 0.94; 95% CI, 0.92-0.96; I2 = 90%; eFigure 4 in Supplement 1) and role functioning (HR, 0.96; 95% CI, 0.94-0.98; I2 = 81%) were associated with improved OS. In contrast, cognitive (HR, 0.96; 95% CI, 0.92-1.00; I2 = 86%), social (HR, 1.01; 95% CI, 0.97-1.05; I2 = 84%), and emotional functioning (HR, 1.04; 95% CI, 0.99-1.10; I2 = 80%) showed no significant association with OS. When all functional scales were pooled, better functioning was associated with improved OS (HR, 0.97; 95% CI, 0.95-0.98; I2 = 88%).

Figure 1. Association Between Global Health Status/Quality of Life (GHQ) Scores and Overall Survival.

Figure 1.

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Reported as hazard ratios (HRs) and 95% CIs. The size of each box reflects the statistical weight of the study in the meta-analysis. Studies are listed by first author, publication year, and cancer type.

Nausea and vomiting (HR, 1.12; 95% CI, 1.04-1.21; I2 = 84%), fatigue (HR, 1.05; 95% CI, 1.00-1.10; I2 = 72%), and pain (HR, 1.07; 95% CI, 1.05-1.10; I2 = 91%) were associated with worse OS (Figure 2). The pooled effect across all symptom scales demonstrated that increasing symptom severity was significantly associated with worse OS (HR, 1.07; 95% CI, 1.05-1.10; I2 = 88%). In addition, the overall pooled effect for single-item symptoms showed a significant association with worse OS (HR, 1.03; 95% CI, 1.01-1.04; I2 = 76%; Figure 3). When examined individually, appetite loss (HR, 1.04; 95% CI, 1.01-1.07; I2 = 86%) and dyspnea (HR, 1.03; 95% CI, 1.00-1.05; I2 = 62%) were associated with worse OS. No significant association between constipation (HR, 1.01; 95% CI, 1.00-1.02) or insomnia (HR, 1.01; 95% CI, 1.00-1.03; I2 = 76%) were identified with OS. One study that reported on diarrhea also reported no significant association with OS (HR, 0.99; 95% CI, 0.89-1.10).59

Figure 2. Association Between European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Symptom Scales Score and Overall Survival.

Figure 2.

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Reported as hazard ratios (HRs) with 95% CIs. Results are presented for fatigue, nausea and vomiting, and pain. The size of each box reflects the statistical weight of the study in the meta-analysis. Studies are listed by first author, publication year, and cancer type.

Figure 3. Association Between European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Single Items and Overall Survival.

Figure 3.

Open in a new tab

Reported as hazard ratios (HRs) and 95% CIs. Results are presented for appetite loss, constipation, diarrhea, dyspnea, and insomnia. The size of each box reflects the statistical weight of the study in the meta-analysis. Studies are listed by first author, publication year, and cancer type.

The Egger test indicated no evidence of publication bias, as illustrated in the funnel plot (eFigure 2 in Supplement 1). The risk of bias assessment, conducted using the Cochrane Risk of Bias 2 tool, is presented in eFigure 3 in Supplement 1. No studies were classified as having a high risk of bias in any domain.

Discussion

This systematic review and meta-analysis of 69 RCTs involving 44 030 patients demonstrated that PROs provide independent prognostic information for OS across diverse cancer populations. The meta-analysis of EORTC QLQ-C30 scales showed that each point increase in GHQ and functional scales was associated with increased OS, while higher symptom burden and specific scale items, such as dyspnea and appetite loss, were associated with worse OS. To our knowledge, this study represents the largest meta-analysis of the literature to date in this setting, quantitatively assessing the association of PROs with OS in patients with cancer. These results suggest that PROs capture unique dimensions of patient health status that complement conventional clinical indicators.

The prognostic significance of GHQ observed in our analysis aligns with Gotay et al,4 who previously identified GHQ measures as the most frequent predictor of survival among PROs. The underlying mechanisms driving this association are likely multifaceted. Patients’ subjective assessment of their overall health status may capture subtle physiological changes that precede clinical detection and potentially reflect underlying tumor biology, disease burden, or systemic responses to cancer. This hypothesis was reinforced by evidence that demonstrated that patients with higher baseline GHQ scores tend to exhibit improved treatment responses.80 Additionally, better self-reported health status may reflect greater physiological and psychological robustness, enabling patients to tolerate treatment regimens with fewer dose modifications or interruptions.81 Moreover, higher GHQ scores may also serve as indicators of proactive health behaviors, including better adherence to prescribed medications, engagement in physical activity, and participation in other health-promoting activities.82 The design of our meta-analysis, which included only RCTs, strengthens the argument that GHQ captures intrinsic prognostic information rather than merely reflecting variations in treatment intensity or physician decision-making.

Our analysis also revealed that physical functioning and role functioning were associated with improved OS. Patient-reported physical functioning may serve as a sensitive indicator of disease burden and progression, potentially detecting subtle declines that are not fully captured by conventional clinical assessments.83 As described by Blazeby et al,84 even subtle deteriorations in physical capability might signal disease progression before becoming apparent through standard imaging or laboratory measures.84 Similarly, role functioning, which assesses patients’ ability to fulfill daily responsibilities and occupational duties, demonstrated independent prognostic significance. Unlike physical functioning, role functioning also encompasses cognitive and emotional dimensions that are required to maintain work responsibilities and social roles.61 Meier et al85 found that in patients with hepatocellular carcinoma, physical and role functioning was associated with survival in univariate analyses, but only role functioning retained significance in multivariate models, suggesting potential distinctive prognostic contributions. These findings reinforce the importance of comprehensive functional assessment in cancer prognostication.

The meta-analysis revealed compelling associations between symptom burden and OS. While nausea and vomiting are common chemotherapy-related adverse effects, affecting 70% to 80% of treated patients,86 their prognostic significance suggests more complex underlying mechanisms.87 Persistent or severe nausea and vomiting can lead to nutritional deficiencies, dehydration, and metabolic imbalances, which may compromise treatment efficacy and contribute to poorer outcomes.87 Additionally, these symptoms can necessitate dose reductions or treatment interruptions, potentially compromising therapeutic efficacy and reducing survival.87 Pain was also associated with survival, reinforcing its role as a clinical marker of symptomatic disease burden.88 Severe pain is often associated with reduced mobility, decreased quality of life, and difficulties in maintaining optimal treatment schedules.88

While our study was not designed to directly compare the prognostic utility of different scales, our findings suggest that the global index appears to be more weakly associated with OS than individual scales. This may be due to patient selection bias, as RCTs typically enroll patients with higher baseline scores. Another possible explanation is that GHQ reflects a broad range of prognostic and nonprognostic factors, diluting its predictive strength compared with more specific functional and symptom scales. While not definitive, this finding suggests differential prognostic utility among PRO scales, reinforcing the need to individualize which measures to prioritize based on patient population characteristics, as well as symptom prevalence and intensity.

The present study extends prior reviews through including updated literature and implementing what is to our knowledge the first comprehensive meta-analysis examining all EORTC QLQ-C30 scales as prognostic indicators.3,4 Whereas Mierzynska et al3 predominantly relied on the frequency of statistically significant associations as their primary analytical framework, our methods were more inclusive, accounting for significant and nonsignificant findings and aggregating all available data to derive comprehensive summary HRs for each domain. Furthermore, our quantitative synthesis methods addressed potential publication bias. For example, social functioning, which ranked fourth in citation frequency as a significant prognostic factor in previous literature,3 was not significantly associated with OS in our meta-analysis, highlighting the need for further investigation within this domain.

Several studies have demonstrated that PROs may provide prognostic information that is comparable with or even superior to traditional clinical factors.13,16,89,90 For instance, in a multivariate analysis of the EORTC 08975 randomized phase 3 trial involving 391 patients with advanced non–small cell lung cancer, Ediebah et al16 found that physical functioning, pain, and dysphagia were independently associated with OS. When these PRO domains were included in the multivariable model, conventional clinical factors, such as histologic subtype and disease stage, were no longer statistically significant.16 Similarly, in a prospective analysis of the RTOG 9801 trial, Movsas et al13 found that baseline GHQ was significantly associated with OS in patients with locally advanced non–small cell lung cancer treated with chemoradiotherapy. When GHQ was included in the multivariable model, traditional prognostic factors, such as Karnofsky performance status, stage, and histology, lost statistical significance. Future research should aim to directly compare HRs of PROs and conventional clinical prognostic variables across different cancer types.

The prognostic value of PROs observed in our study supports their integration into multidisciplinary cancer conferences and clinical decision-making frameworks.91 PROs could be incorporated into predictive models, potentially leveraging advances in artificial intelligence, to develop more accurate survival prediction tools that combine clinical, biological, and patient-reported factors.92 Furthermore, systematic assessment of PROs may identify patients at heightened risk for treatment discontinuation, a critical consideration given that patient preference and toxic effects have been shown to be associated with premature chemotherapy cessation.93

Limitations

Despite the strengths of this study, several limitations should be acknowledged. While we restricted our analysis to RCTs to enhance methodological rigor, variability in trial design, patient populations, and cancer types may have contributed to heterogeneity in our findings. Because RCT populations are often more selective than clinical cohorts, the prognostic associations we observed may differ in routine clinical practice, where patients typically present with a poorer performance status. Although we used a random-effects model to account for between-study variability, residual confounding remains a possibility. The reliance on published HRs from multivariate models also limited our ability to assess potential differences in adjustment strategies across studies, as the covariates controlled for varied, and some models adjusted for multiple PRO domains, while others used separate models for each PRO. This study was not designed to directly compare the relative prognostic strength of different PRO domains. While we observed numerical differences in HRs across domains, overlapping confidence intervals and the absence of head-to-head statistical comparisons limited our ability to definitively rank the prognostic strength of different PRO measures. Our meta-analysis also focused exclusively on the EORTC QLQ-C30, the most widely validated and used PRO instrument in oncology; however, other PRO measures, such as the Functional Assessment of Cancer Therapy and EuroQol 5-Dimension scale, may provide additional prognostic insights. Additionally, individual patient data meta-analysis may provide more granular insights into the prognostic value of PROs and facilitate standardized adjustment for confounders across studies.

Conclusions

This systematic review and meta-analysis of 69 RCTs involving 44 030 patients provided quantitative evidence that PROs offer independent prognostic information for OS for patients with cancer. Our findings demonstrated that higher baseline scores in GHQ and functional domains, particularly physical and role functioning, are associated with improved survival, while greater symptom burden is associated with worse outcomes. These results highlight the unique prognostic value of PROs in complementing traditional clinical and disease-related factors, underscoring their potential role in risk stratification and treatment decision-making in oncology.

Supplement 1.

eTable 1. Search Strategy for Pubmed (MEDLINE)

eTable 2. Summary of Studies Examining Patient-Reported Outcomes and Overall Survival Using Multivariable Analysis in Cancer Patients

eTable 3. Summary of Patient-Reported Outcome Domains Included as Covariates in Multivariable Models Across Studies Included in Meta-Analysis

eFigure 1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flowchart of included studies

eFigure 2. Funnel plot examining publication bias

eFigure 3. Risk of bias evaluated using Cochrane’s Risk of Bias 2 (RoB 2) assessment tool for randomized controlled trials

eFigure 4. Forest plots showing the associations between EORTC QLQ-C30 functional scales and overall survival, reported as hazard ratios with 95% confidence intervals

jamaoncol-e253153-s001.pdf (2.3MB, pdf)
Supplement 2.

Data sharing statement

jamaoncol-e253153-s002.pdf (16.3KB, pdf)

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement 1.

eTable 1. Search Strategy for Pubmed (MEDLINE)

eTable 2. Summary of Studies Examining Patient-Reported Outcomes and Overall Survival Using Multivariable Analysis in Cancer Patients

eTable 3. Summary of Patient-Reported Outcome Domains Included as Covariates in Multivariable Models Across Studies Included in Meta-Analysis

eFigure 1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flowchart of included studies

eFigure 2. Funnel plot examining publication bias

eFigure 3. Risk of bias evaluated using Cochrane’s Risk of Bias 2 (RoB 2) assessment tool for randomized controlled trials

eFigure 4. Forest plots showing the associations between EORTC QLQ-C30 functional scales and overall survival, reported as hazard ratios with 95% confidence intervals

jamaoncol-e253153-s001.pdf (2.3MB, pdf)
Supplement 2.

Data sharing statement

jamaoncol-e253153-s002.pdf (16.3KB, pdf)

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