Reporting and Guidelines in Propensity Score Analysis: A Systematic Review of Cancer and Cancer Surgical Studies.

Background: : Propensity score (PS) analysis is increasingly being used in observational studies, especially in some cancer studies where random assignment is not feasible. This systematic review evaluates the use and reporting quality of PS analysis in oncology studies. Methods: : We searched PubMed to identify the use of PS methods in cancer studies (CS) and cancer surgical studies (CSS) in major medical, cancer, and surgical journals over time and critically evaluated 33 CS published in top medical and cancer journals in 2014 and 2015 and 306 CSS published up to November 26, 2015, without earlier date limits. The quality of reporting in PS analysis was evaluated. It was also compared over time and among journals with differing impact factors. All statistical tests were two-sided. Results: More than 50% of the publications with PS analysis from the past decade occurred within the past two years. Of the studies critically evaluated, a considerable proportion did not clearly provide the variables used to estimate PS (CS 12.1%, CSS 8.8%), incorrectly included non baseline variables (CS 3.4%, CSS 9.3%), neglected the comparison of baseline characteristics (CS 21.9%, CSS 15.6%), or did not report the matching algorithm utilized (CS 19.0%, CSS 36.1%). In CSS, the reporting of the matching algorithm improved in 2014 and 2015 ( P = .04), and the reporting of variables used to estimate PS was better in top surgery journals ( P = .008). However, there were no statistically significant differences for the inclusion of non baseline variables and reporting of comparability of baseline characteristics. Conclusions: The use of PS in cancer studies has dramatically increased recently, but there is substantial room for improvement in the quality of reporting even in top journals. Herein we have proposed reporting guidelines for PS analyses that are broadly applicable to different areas of medical research that will allow better evaluation and comparison across studies applying this approach.

Enrollment Trends and Disparity Among Patients With Lung Cancer in National Clinical Trials, 1990 to 2012.

Purpose Under-representation of elderly, women, and racial/ethnic minority patients with cancer in clinical trials is of national concern. The goal of this study was to characterize enrollment trends and disparities by age, sex, and race/ethnicity in lung cancer trials. Methods We analyzed data for 23,006 National Cancer Institute cooperative group lung cancer trial participants and 578,476 patients with lung cancer from the SEER registry from 1990 to 2012. The enrollment disparity difference (EDD) and enrollment disparity ratio (EDR) were calculated on the basis of the proportion of each subgroup in the trial population and the US lung cancer population. Annual percentage changes (APCs) in the subgroup proportions in each population were compared over time. Results Enrollment disparity for patients ≥ 70 years of age with non-small-cell lung cancer improved from 1990 to 2012 (test of parallelism, P = .020), with a remaining EDD of 0.22 (95% CI, 0.19 to 0.25) and EDR of 1.65 (95% CI, 1.51 to 1.82) in 2010 to 2012. No improvement was seen for elderly patients with small-cell lung cancer (SCLC), with an APC of 0.20 ( P = .714) among trial participants, despite a rising proportion of elderly patients with SCLC in the US population (APC, 0.32; P = .020). Enrollment disparity for women with lung cancer improved overall, with the gap closing by 2012 (EDD, 0.03 [95% CI, 0.00 to 0.06]; EDR, 1.07 [95% CI, 1.00 to 1.16]). Enrollment disparities persisted without significant improvement for elderly women, blacks, Asians/Pacific Islanders, and Hispanics. Conclusion Under-representation in lung cancer trials improved significantly from 1990 to 2012 for elderly patients with non-small-cell lung cancer and for women, but ongoing efforts to improve the enrollment of elderly patients with SCLC and minorities are needed. Our study highlights the importance of addressing enrollment disparities by demographic and disease subgroups to better target under-represented groups of patients with lung cancer.