A systematic review of the quality of conduct and reporting of survival analyses of tuberculosis outcomes in Africa

Abstract

Background Survival analyses methods (SAMs) are central to analysing time-to-event outcomes. Appropriate application and reporting of such methods are important to ensure correct interpretation of the data. In this study, we systematically review the application and reporting of SAMs in studies of tuberculosis (TB) patients in Africa. It is the first review to assess the application and reporting of SAMs in this context. Methods Systematic review of studies involving TB patients from Africa published between January 2010 and April 2020 in English language. Studies were eligible if they reported use of SAMs. Application and reporting of SAMs were evaluated based on seven author-defined criteria. Results Seventy-six studies were included with patient numbers ranging from 56 to 182,890. Forty-three (57%) studies involved a statistician/epidemiologist. The number of published papers per year applying SAMs increased from two in 2010 to 18 in 2019 (P = 0.004). Sample size estimation was not reported by 67 (88%) studies. A total of 22 (29%) studies did not report summary follow-up time. The survival function was commonly presented using Kaplan-Meier survival curves (n = 51, (67%) studies) and group comparisons were performed using log-rank tests (n = 44, (58%) studies). Sixty seven (91%), 3 (4.1%) and 4 (5.4%) studies reported Cox proportional hazard, competing risk and parametric survival regression models, respectively. A total of 37 (49%) studies had hierarchical clustering, of which 28 (76%) did not adjust for the clustering in the analysis. Reporting was adequate among 4.0, 1.3 and 6.6% studies for sample size estimation, plotting of survival curves and test of survival regression underlying assumptions, respectively. Forty-five (59%), 52 (68%) and 73 (96%) studies adequately reported comparison of survival curves, follow-up time and measures of effect, respectively. Conclusion The quality of reporting survival analyses remains inadequate despite its increasing application. Because similar reporting deficiencies may be common in other diseases in low- and middle-income countries, reporting guidelines, additional training, and more capacity building are needed along with more vigilance by reviewers and journal editors.

Social Inequalities in Mental Health and Self-Perceived Health in the First Wave of COVID-19 Lockdown in Latin America and Spain: Results of an Online Observational Study

“…Younger people had the highest prevalence of anxiety and depression, especially in women, decreasing in older people in all countries, except for men in Peru. These results are consistent with other studies that showed a decrease in the occurrence of mental health problems with increasing age [ 54 ], despite the fact that COVID-19 threatens the physical health of the older population, related to social issues [ 43 ]. In LA, educational centers were closed for an average of more than 1 year, and, despite the boost of virtual classes, this situation increased the effects of the digital divide and emotional apathy [ 20 ].…”

Using fractional polynomials and restricted cubic splines to model non‐proportional hazards or time‐varying covariate effects in the Cox regression model

“…In a review of papers published in the cancer literature in an earlier period and whose findings may not pertain to current statistical practice, Altman et al 2 found that only 5% of papers assessed whether the assumptions of the Cox model were satisfied. Ngari et al 3 examined the quality of survival analyses in studies of tuberculosis outcomes published between 2010 and 2020. Of the 67 studies that reported using a Cox proportional hazards model, 32 (48%) stated that the proportional hazards assumption had been tested, while only 2 (3%) reported the results of such a test.…”