Prognostic evaluation and treatment strategies for cervical cancer in pregnancy: a systematic review and meta-analysis

妊娠期宫颈癌的预后评估和治疗策略:系统评价和荟萃分析

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Abstract

ABTSTRAC: OBJECTIVE: This study was conducted to evaluate the prognosis of cervical cancer in pregnancy (CCIP) and analyze the clinicopathological factors affecting the prognosis of this cancer. DATA SOURCES: The studies published through July 2024 were systematically retrieved from PubMed, Embase, Web of Science, and Cochrane Library. STUDY ELIGIBILITY CRITERIA: The cohort studies, case-control studies, randomized controlled trials, and non-randomized controlled trials involving CCIP patients with data on 5-year overall survival (OS) were included in this study. STUDY APPRAISAL AND SYNTHESIS METHODS: The quality of the included studies was assessed using the Newcastle-Ottawa Scale (NOS). A meta-analysis was performed using Stata 15.0, focusing on the 5-year OS and relevant clinicopathological factors. RESULTS: The results demonstrated that the 5-year OS of patients with CCIP was similar to that of non-pregnant patients with cervical cancer (RR = 1.00, 95% CI: 0.94-1.06, P = 0.978). The subgroup analysis results revealed that tumor size (≥ 4 cm), International Federation of Gynecology and Obstetrics (FIGO) stage (≥ IB2), and timing of diagnosis (postpartum) were prognostic factors with statistical significance (P < 0.05). However, such factors as pregnancy termination and timing of delivery did not significantly affect the 5-year OS (P > 0.05). The delivery mode required further validation despite its borderline significance (P = 0.05). CONCLUSION: The results of this study suggest that pregnancy does not exert a significant adverse effect on the long-term survival of patients with cervical cancer. Tumor size (≥ 4 cm), FIGO stage (≥ IB2), and time of diagnosis (postpartum) are identified as unfavorable prognostic factors for CCIP patients, while delivery mode requires further investigation. These findings provide strong evidence to support the optimization of personalized treatment strategies for CCIP patients.

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