Global variation in postoperative mortality and complications after cancer surgery: a multicentre, prospective cohort study in 82 countries

Abstract

Background: 80% of individuals with cancer will require a surgical procedure, yet little comparative data exist on early outcomes in low-income and middle-income countries (LMICs). We compared postoperative outcomes in breast, colorectal, and gastric cancer surgery in hospitals worldwide, focusing on the effect of disease stage and complications on postoperative mortality.

Methods: This was a multicentre, international prospective cohort study of consecutive adult patients undergoing surgery for primary breast, colorectal, or gastric cancer requiring a skin incision done under general or neuraxial anaesthesia. The primary outcome was death or major complication within 30 days of surgery. Multilevel logistic regression determined relationships within three-level nested models of patients within hospitals and countries. Hospital-level infrastructure effects were explored with three-way mediation analyses. This study was registered with ClinicalTrials.gov, NCT03471494.

Findings: Between April 1, 2018, and Jan 31, 2019, we enrolled 15 958 patients from 428 hospitals in 82 countries (high income 9106 patients, 31 countries; upper-middle income 2721 patients, 23 countries; or lower-middle income 4131 patients, 28 countries). Patients in LMICs presented with more advanced disease compared with patients in high-income countries. 30-day mortality was higher for gastric cancer in low-income or lower-middle-income countries (adjusted odds ratio 3·72, 95% CI 1·70-8·16) and for colorectal cancer in low-income or lower-middle-income countries (4·59, 2·39-8·80) and upper-middle-income countries (2·06, 1·11-3·83). No difference in 30-day mortality was seen in breast cancer. The proportion of patients who died after a major complication was greatest in low-income or lower-middle-income countries (6·15, 3·26-11·59) and upper-middle-income countries (3·89, 2·08-7·29). Postoperative death after complications was partly explained by patient factors (60%) and partly by hospital or country (40%). The absence of consistently available postoperative care facilities was associated with seven to 10 more deaths per 100 major complications in LMICs. Cancer stage alone explained little of the early variation in mortality or postoperative complications.

Interpretation: Higher levels of mortality after cancer surgery in LMICs was not fully explained by later presentation of disease. The capacity to rescue patients from surgical complications is a tangible opportunity for meaningful intervention. Early death after cancer surgery might be reduced by policies focusing on strengthening perioperative care systems to detect and intervene in common complications.

Funding: National Institute for Health Research Global Health Research Unit.

Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.

Figures

Figure 1

Patient flow chart

Figure 2

Patients and outcomes by cancer type and country income group Data are for 15 958 patients from 82 countries and 428 hospitals. Crude outcome rates are shown for 30-day mortality, 30-day major complication (Clavien-Dindo grade ≥III), and 30-day any complication.

Figure 3

Stage of presentation (A), 30-day mortality (B), and 30-day complications (C) by cancer and country income group (A) Proportion of patients enrolled by cancer stage by country income group. (B) Proportion of patients dying or sustaining a major complication or any complication by day 30 after surgery stratified by country income group. (C) Proportion of patients sustaining a major complication who died within 30 days.

Figure 4

Multilevel logistic regression-adjusted outcomes by World Bank country income group Models were built incorporating patient and disease factors specific to each cancer. Univariable, full multivariable, parsimonious multivariable, and multilevel (patient, hospital, country) models for each outcome in each cancer type are given in the appendix (pp 22–38). Box size proportional to group size (n). WB=World Bank. OR=odds ratio.

Figure 5

Capacity to rescue from major complication (A) Multilevel logistic regression model for predictors of death after major complication in colorectal and gastric cancer. Box size proportional to group size (n). (B) Three-way decomposition mediation model of the proportion of the effect of country income group on 30-day mortality mediated by postoperative care infrastructure (the consistent presence of a designated postoperative recovery area, the availability of critical care facilities, and the existence of a working CT scanner). (C) Proportion of 30-day mortality variation explained at the level of patient or disease, hospital, country, and country income group, in patients with colorectal or gastric cancer who died after major complication. The variance explained at each of the four levels of the model (marginal pseudo R2) is expressed as a proportion of the total variance explained (conditional pseudo R2). (D) Absolute risk difference for 30-day mortality after major complication in the presence of consistently available postoperative care infrastructure. Estimates for age 55 years, ECOG performance status 1, ASA grade 2, cancer stage II, and elective surgery. WB=World Bank. OR=odds ratio. ECOG=Eastern Cooperative Oncology Group. ASA=American Society of Anesthesiologists.