Objective To evaluate the reporting quality and influencing factors of patient-reported outcome (PRO) data in randomized controlled trials (RCTs) of lung cancer. Methods RCTs of lung cancer with PRO as either primary or secondary endpoints were searched from PubMed, EMbase, Medline, CNKI, Wanfang Data, and VIP databases between January 1, 2010 and April 20, 2024. Reporting quality of included RCTs were assessed based on the CONSORT-PRO extension. Descriptive statistics and bivariate regression analysis were used to describe the reporting quality and analyze the factors influencing the reporting quality. Results A total of 740 articles were retrieved. After screening, 53 eligible RCTs of lung cancer with 22 780 patients were included. The patients were mainly with non-small cell lung cancer (84.91%), with the median sample size of the included studies was 364.0 (160.5, 599.5) patients. The primary PRO tool used was the EORTC QLQ-C30 (60.38%). There were 52 (98.11%) studies whose PRO measured the domain of "symptom management of cough, dyspnea, fatigue, pain, etc.", and 45 (84.91%) studies measured "health-related quality of life". Multicenter studies accounted for 84.91%, and randomized non-blind trials accounted for 62.26%. PRO was used as the primary endpoint in 33.96% of the studies and as secondary endpoints in 66.04%. The reliability and validity of the PRO tools were explicitly mentioned in 11.32% and 7.55% of the studies, respectively. The average completeness of reporting according to the CONSORT-PRO guidelines was 60.00%, ranging from 25.00% to 93.00%. The main factors affecting the completeness of CONSORT-PRO reporting included sample size and publication year. For every increment in sample size, the completeness of reporting increased by 27.5% (SE=0.00, t=2.040, P=0.046). Additionally, studies published after 2018 had a 67.2% higher completeness of reporting compared to those published in or before 2018 (SE=17.8, t=–3.273, P=0.006). Conclusion The study reveals that the overall reporting quality of PRO in lung cancer RCTs is poor. Particularly, the reporting of PRO measures reliability and validity, PRO assumptions, applicability, and handling of missing data need further improvement. Future research should emphasize comprehensive adherence to the CONSORT-PRO guidelines.
ObjectiveTo categorize and describe stroke-patients based on factors related to patient reported outcomes. MethodsA questionnaire survey was conducted among stroke-patients in nine hospitals and communities in Shanxi Province. The general information questionnaire and stroke-patient reported outcome manual (Stroke-PROM) were completed. Latent profile analysis was used to analyze the scores of Stroke-PROM, and the explicit variables of the model were the final scores of each dimension. ANOVA and correlation analysis were used to measure the correlation between the factors and subtypes. ResultsFour unique stroke-patient profiles emerged, including a low physiological and low social group (9%), a high physiological and middle social group (40%), a middle physiological and middle social group (26%), and a middle physiological and high social group (25%). There were significant differences in scores of four areas among patients with different subtypes (P<0.05). Moreover, there was a correlation between age, payment, exercise and subtypes (P<0.05). ConclusionThere are obvious grouping characteristics for stroke patients. It is necessary to focus on stroke patients who are advanced in age, have a self-funded status and lack exercise, and provide targeted nursing measures to improve their quality of life.
Patient reported outcome measures (PROM) are widely used in clinical research and practice. To aid the interpretation of PROM, researchers have proposed the minimal important difference (MID), the smallest change or difference that patients perceive as important. However, the estimation methods of MID are numerous and inconsistent, which brings difficulties to selecting the optimal MID estimate to interpret PROM results. To address this issue, a research team from McMaster University in Canada has proposed an approach for selecting the optimal MID. This method includes three core steps: evaluating the credibility of MID estimates, assessing the consistency among credible MID estimates, and selecting the optimal value based on contextual factors. The credibility evaluation instrument for anchor-based MID examines five core criteria, including the data sources of PROM and anchor, the interpretability of anchor, the correlation between anchor and PROM, the precision of MID estimates, and the judgment of anchor thresholds. When there are multiple credible MID estimates, the optimal MID estimate is selected by evaluating the consistency among the estimates and considering contextual factors that affect the variability among the estimates, such as the type of intervention, follow-up time, and disease severity. In addition, the team provided recommendations to improve the reporting quality of MID studies. This article provides a detailed introduction and interpretation of these developments, aiming to enhance researchers' and clinicians' understanding and application of MID, thereby supporting clinical research and healthcare decision-making.
Systematic evaluation of patient-reported outcome measures (PROMs) is crucial for identifying high-quality PROMs for research and clinical practice. It ensures reliable health outcomes data collection. But current PROMs systematic evaluation reports vary in quality and have many defects. To address this, in 2024, the guideline research team updated and published the COSMIN guideline V2.0 for PROMs systematic evaluation and two other tools in the Quality of Life Research. This paper interprets the guideline development team, method, and the core content of the COSMIN guideline V2.0. It also uses specific examples to promote standardized PROMs selection and clinical application, aiming to help domestic researchers improve the quality of such systematic evaluations.
In recent years, the Chengdu Municipal Thoracic Surgery Quality Control Center has preliminarily established a regional quality control system for thoracic surgery through the development of standards, data reporting, and on-site supervision, achieving phased improvements. This review summarizes the current development of Chengdu’s thoracic surgery quality control system, including its organizational structure and scoring methodology, quality indicators based on structure–process–outcome, information technology infrastructure, and multicenter collaboration experiences, and outlines trends in surgical volume, minimally invasive procedure rates, human resources, and care quality metrics. It also analyzes existing challenges such as inter-hospital quality disparities and insufficient interoperability among information platforms. Drawing on domestic and international best practices, we propose development strategies to further enhance the homogenization and continuous improvement of thoracic surgery quality in the region. The Chengdu experience could offer a valuable model for building regional thoracic surgery quality control systems nationwide and for integration with the national quality control platform.
Cardiac surgery is often associated with significant trauma, which can lead to a suboptimal recovery experience for patients. With advancements in cardiovascular surgical techniques, the rates of surgical mortality and complications have significantly decreased, leading to increased attention on patients' subjective recovery experiences after the surgery. Patient-reported outcomes (PROs) refer to the feedback provided directly by patients regarding their health status, functional abilities, and treatment experiences. Accurate assessment and timely intervention of PROs have become a growing area of interest in the academic community, with improvements in certain PROs showing significant correlations with prognostic benefits. However, there remains controversy regarding which dimensions of PROs should be prioritized in the postoperative recovery of cardiac surgery patients and how to select appropriate evaluation scales for these dimensions. We referenced the research progress both domestically and internationally, combined with clinical practices from around the world, and widely solicited expert opinions to reach a consensus on the evaluation dimensions of postoperative PROs for cardiac surgery patients. This includes the overall recovery status of patients (surgical recovery, quality of life) and its nine dimensions (pain, physiology, sleep, thirst, frailty, activity, cognition, mental health, and social support). This consensus comprehensively considers the application of PROs scales, and introduces 1-3 scales with the widest application and most solid evidence for each dimension, aiming to further standardize the evaluation dimensions of PROs after cardiac surgery in China and the selection of scales for each dimension.
Measurement properties studies of patient-reported outcome measures (PROMs) aims to validate the measurement properties of PROMs. In the process of designing and statistical analysis of these measurement properties studies, bias will occur if there are any defects, which will affect the quality of PROMs. Therefore, the COSMIN (consensus-based standards for the selection of health measurement instruments) team has developed the COSMIN risk of bias (COSMIN-RoB) checklist to evaluate risk of bias of studies on measurement properties of PROMs. The checklist can be used to develop systematic reviews of PROMs measurement properties, and for PROMs developers, it can also be used to guide the research design in the measurement tool development process for reducing bias. At present, similar assessment tools are lacking in China. Therefore, this article aims to introduce the primary contents of COSMIN-RoB checklist and to interpret how to evaluate risk of bias of the internal structure studies of PROMs with examples.
The COSMIN-RoB checklist includes three sections with a total of 10 boxes, which is used to evaluate risk of bias of studies on content validity, internal structure, and other measurement properties. COSMIN classifies reliability, measurement error, criteria validity, hypothesis testing for construct validity, and responsiveness as other measurement properties, which primarily focus on the quality of the (sub)scale as a whole, rather than on the item level. Among the five measurement properties, reliability, measurement error and criteria validity are the most widely used in the studies. Therefore, this paper aims to interpret COSMIN-RoB checklist with examples to guide researchers to evaluate the risk of bias of the studies on reliability, measurement error and criteria validity of PROMs.
Patient-reported outcome (PRO) has been paid increasing attention in lung cancer surgery. It has gradually become an important outcome indicator in clinical research of lung cancer surgery and an important tool for symptom management. Commonly used lung cancer-specific PRO measurement tools include: Lung Cancer Symptom Scale, European Organization for Research and Treatment of Cancer-Core Quality of Life Questionnaire and Lung Cancer module, Functional Assessment of Cancer Therapy-Lung, MD Anderson Symptom Inventory-Lung Cancer module, Postoperative Symptom Scale for Lung Cancer Patients, and Perioperative Symptom Assessment for Lung Surgery. The application of lung cancer-specific scales lacks authoritative implementation norms in the field of lung cancer surgery in terms of scale selection, data collection, and outcome application. This review aimed to analyze the current status of application of PRO scales in lung cancer surgery.