Early Non-Response to Neoadjuvant Chemotherapy Will Increase the Recurrence of Cervical Cancer: A Systematic Review

Objectives: Cervical cancer remains a significant global health burden for women. While neoadjuvant chemotherapy (NACT) has emerged as a potential treatment option, the prognostic implications of early non-response to NACT remain inadequately characterized. This systematic review aims to elucidate the association between early non-response to NACT and long-term disease-free survival (DFS) in cervical cancer patients. Methods: A comprehensive systematic review was conducted following PRISMA guidelines. PubMed, Embase, Elsevier, Springer, EBSCO, and Cochrane Library were systematically searched to identify eligible studies. Pooled hazard ratios (HRs) for DFS with 95% confidence intervals (CIs) were calculated using R software (version 4.5.1). Heterogeneity was assessed via Cochran’s Q test and I2 statistics. Publication bias was evaluated using funnel plots, Begg’s test, Egger’s test, and trim-and-fill methods. Sensitivity analyses further validated result robustness. Results: Eleven studies (n = 2064 patients; 1546 responders, 518 non-responders) met inclusion criteria. The pooled early non-response rate ranged from 13% to 39%. Early non-response significantly correlated with poorer DFS (HR = 3.29, 95% CI 2.35–4.62). Subgroup analyses by response criteria showed HRs of 2.94 (95% CI 1.72–5.03) for WHO criteria and 4.00 (95% CI 2.52–6.34) for RECIST criteria. No significant publication bias was detected (Begg’s p = 0.35; Egger’s p = 0.28). Sensitivity analyses and trim-and-fill adjustments confirmed result stability. Conclusions: Early non-response to NACT predicts worse DFS in women with cervical cancer. These findings proposed the need for large-scale or prospective studies to validate the prognostic value of early non-response and optimize treatment strategies for non-responders. Future prospective trials with standardized protocols are essential to validate these findings and establish criteria for optimizing patient selection for NACT-based therapeutic strategies.