Parker Tope

The impact of lag time to cancer diagnosis and treatment on clinical outcomes prior to the COVID-19 pandemic: A scoping review of systematic reviews and meta-analyses

Background: The COVID-19 pandemic has disrupted cancer care, raising concerns regarding the impact of wait time, or ‘lag time’, on clinical outcomes. We aimed to contextualize pandemic-related lag times by mapping pre-pandemic evidence from systematic reviews and/or meta-analyses on the association between lag time to cancer diagnosis and treatment with mortality- and morbidity-related outcomes. Methods: We systematically searched MEDLINE, EMBASE, Web of Science, and Cochrane Library of Systematic Reviews for reviews published prior to the pandemic (1 January 2010–31 December 2019). We extracted data on methodological characteristics, lag time interval start and endpoints, qualitative findings from systematic reviews, and pooled risk estimates of mortality- (i.e., overall survival) and morbidity- (i.e., local regional control) related outcomes from meta-analyses. We categorized lag times according to milestones across the cancer care continuum and summarized outcomes by cancer site and lag time interval. Results: We identified 9032 records through database searches, of which 29 were eligible. We classified 33 unique types of lag time intervals across 10 cancer sites, of which breast, colorectal, head and neck, and ovarian cancers were investigated most. Two systematic reviews investigating lag time to diagnosis reported different findings regarding survival outcomes among paediatric patients with Ewing’s sarcomas or central nervous system tumours. Comparable risk estimates of mortality were found for lag time intervals from surgery to adjuvant chemotherapy for breast, colorectal, and ovarian cancers. Risk estimates of pathologic complete response indicated an optimal time window of 7–8 weeks for neoadjuvant chemotherapy completion prior to surgery for rectal cancers. In comparing methods across meta-analyses on the same cancer sites, lag times, and outcomes, we identified critical variations in lag time research design. Conclusions: Our review highlighted measured associations between lag time and cancer-related outcomes and identified the need for a standardized methodological approach in areas such as lag time definitions and accounting for the waiting-time paradox. Prioritization of lag time research is integral for revised cancer care guidelines under pandemic contingency and assessing the pandemic’s long-term effect on patients with cancer. Funding: The present work was supported by the Canadian Institutes of Health Research (CIHR-COVID-19 Rapid Research Funding opportunity, VR5-172666 grant to Eduardo L. Franco). Parker Tope, Eliya Farah, and Rami Ali each received an MSc. stipend from the Gerald Bronfman Department of Oncology, McGill University.

Ecologic Analysis of Correlates of Cervical Cancer Morbidity and Mortality in Sub-Saharan Africa

Abstract Background: Cervical cancer is the fourth leading cause of death among women worldwide, with 85% of the burden falling on low- to middle- income countries. We studied the correlates of cervical cancer incidence and mortality, and case-fatality in Sub-Saharan Africa. Methods: Country-level data on 16 putative cervical cancer correlates for 37 Sub-Saharan African countries were collected from publicly available data sources. We performed univariate and multiple (stepwise) linear regression analyses to identify correlates of cervical cancer incidence and mortality, and case-fatality. Results: In univariate analyses, incidence and mortality rates were significantly correlated with contraceptive use, penile cancer incidence, and human immunodeficiency virus prevalence. Incidence rates were also correlated with literacy rates, whereas mortality rates were correlated with the proportion of rural population and screening coverage. Multiple regression analyses showed contraceptive use (P = 0.009) and penile cancer incidence (P = 0.004) as associated with cervical cancer incidence. Penile cancer incidence (P = 9.77 × 10–5) and number of medical doctors (P = 0.0433) were associated with mortality. The goodness of fit of the incidence and mortality models was moderate at best, explaining 49% and 37% of variability in the data, respectively. However, the case-fatality model had the best fit explaining most of the variation (adjusted R2 = 0.948; P = 6.822 × 10–16). Conclusions: To reduce the burden of cervical cancer in Sub-Saharan Africa, it would be important to design multimodal interventions that not only target screening and HPV vaccination, but also focus on cervical cancer correlates. Impact: Identifying contextual factors associated with cervical cancer in this region could inform targeted interventions.