Patient-Reported Outcomes as Independent Prognostic Factors for Survival in Oncology: Systematic Review and Meta-Analysis

ObjectivesAssessment of patient-reported outcomes (PROs) in oncology is of critical importance because it provides unique information that may also predict clinical outcomes.MethodsWe conducted a systematic review of prognostic factor studies to examine the prognostic value of PROs for survival in cancer. A systematic literature search was performed in PubMed for studies published between 2013 and 2018. We considered any study, regardless of the research design, that included at least 1 PRO domain in the final multivariable prognostic model. The protocol (EPIPHANY) was published and registered in the International Prospective Register of Systematic Reviews (CRD42018099160).ResultsEligibility criteria selected 138 studies including 158 127 patients, of which 43 studies were randomized, controlled trials. Overall, 120 (87%) studies reported at least 1 PRO to be statistically significantly prognostic for overall survival. Lung (n = 41, 29.7%) and genitourinary (n = 27, 19.6%) cancers were most commonly investigated. The prognostic value of PROs was investigated in secondary data analyses in 101 (73.2%) studies. The EORTC QLQ-C30 questionnaire was the most frequently used measure, and its physical functioning scale (range 0-100) the most frequent independent prognostic PRO, with a pooled hazard ratio estimate of 0.88 per 10-point increase (95% CI 0.84-0.92).ConclusionsThere is convincing evidence that PROs provide independent prognostic information for overall survival across cancer populations and disease stages. Further research is needed to translate current evidence-based data into prognostic tools to aid in clinical decision making.     

Feasibility of health-related quality of life (HRQoL) assessment for cancer patients using electronic patient-reported outcome (ePRO) in daily clinical practice

Quality of Life Research - Routine Electronic Monitoring of Health-Related Quality of Life (HRQoL) (REMOQOL) in clinical care with real-time feedback to physicians could help to enhance...     

Modeling strategies to improve parameter estimates in prognostic factors analyses with patient-reported outcomes in oncology

Purpose

The inclusion of patient-reported outcome (PRO) questionnaires in prognostic factor analyses in oncology has substantially increased in recent years. We performed a simulation study to compare the performances of four different modeling strategies in estimating the prognostic impact of multiple collinear scales from PRO questionnaires.

Methods

We generated multiple scenarios describing survival data with different sample sizes, event rates and degrees of multicollinearity among five PRO scales. We used the Cox proportional hazards (PH) model to estimate the hazard ratios (HR) using automatic selection procedures, which were based on either the likelihood ratio-test (Cox-PV) or the Akaike Information Criterion (Cox-AIC). We also used Cox PH models which included all variables and were either penalized using the Ridge regression (Cox-R) or were estimated as usual (Cox-Full). For each scenario, we simulated 1000 independent datasets and compared the average outcomes of all methods.

Results

The Cox-R showed similar or better performances with respect to the other methods, particularly in scenarios with medium–high multicollinearity (ρ?=?0.4 to ρ?=?0.8) and small sample sizes (n?=?100). Overall, the Cox-PV and Cox-AIC performed worse, for example they did not select one or more prognostic collinear PRO scales in some scenarios. Compared with the Cox-Full, the Cox-R provided HR estimates with similar bias patterns but smaller root-mean-squared errors, particularly in higher multicollinearity scenarios.

Conclusions

Our findings suggest that the Cox-R is the best approach when performing prognostic factor analyses with multiple and collinear PRO scales, particularly in situations of high multicollinearity, small sample sizes and low event rates.

     

Consensus Patients pour des REcherches en soins de Support : projet CyPRES

In oncology, supportive care should be used along with curative treatment or palliative care in order to improve patients’ health-related quality of life, overall survival, and to better support treatment side effects as well as the disease evolution. Unfortunately, they are not widely used in clinical practice. A direct assessment of the needs perceived as unmet by patients could help to assess the magnitude of expectations to better target treatments as an example. A prospective assessment of the expectations and needs of the patients is thus essential. This would also help to highlight the convergence between the supportive care proposed and used and that expected by patients. The first step to understanding how to optimize the use of resources and to improve the quality of care is to identify patient’s expectations. Moreover, it is now well recognized that patients should play a key role in research and that their active participation in research can increase the relevance of the research. In this context, the CyPRES project aims to: 1) assess through national consensus, patients’ expectations in terms of supportive care in order to help both clinicians and health care services; 2) prioritize patients’ expectations and arrange resources according to the priority needs identified; 3) identify supportive care for which no previous research (evidence-based medicine) has demonstrated their usefulness. A randomized clinical trial will thus be proposed; 4) involve patients in the writing, conduct, and analyses, as well as communications of the randomized clinical trial. Using two questionnaires sequentially administered through a modified DELPHI consensus method with RAND scoring, supportive care considered as priority to patients will be identified.     

Economic Burden of Metastatic Clear-Cell Renal Cell Carcinoma for French Patients Treated With Targeted Therapies

Background

Targeted therapies have transformed the treatment of metastatic clear-cell renal cell carcinoma (mccRCC). Despite the importance of mccRCC, studies on its economic burden in daily practice are sparse. The purpose of this retrospective study was to evaluate cost of illness for 224 patients with mccRCC included in the cohort published by Thiery-Vuillemin et al (Factors influencing overall survival for patients with metastatic clear-cell renal cell-carcinoma in daily practice. Clin Genitourin Cancer 2018; 16:e297-305), and then to determine the explanatory factors of cost of illness.