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Updated: Aug 16, 2026

Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence
Published on: October 25, 2011
The prognostic value of growth pattern-based grading for mucinous ovarian carcinoma (MOC): a systematic review and
Mengmeng Chen1,2, Ling Han1,2, Yisi Wang1,2
1Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University, Sichuan, China.
Objective:
To investigate the prognostic significance of expansile and infiltrative growth patterns in mucinous ovarian carcinoma (MOC).
Methods:
A systematic search was conducted in the PubMed, Embase, and Web of Science databases for studies published between January 1, 2010, and September 6, 2024, examining the correlation between expansile and infiltrative tumor growth patterns and prognosis in MOC. Subgroup analyses were performed for mortality, recurrence, and FIGO stage I based on tumor subtype. The Chi-square test was used to evaluate the distribution of expansile and infiltrative tumors across FIGO stages I-IV.
Results:
Twelve eligible studies, comprising a total of 1185 patients, were included in this systematic review and meta-analysis. The combined death rate in the expansile and infiltrative MOC was 10.5% (95%CI: 6.2-15.7) and 31.1% (95%CI: 14.1-50.9). The combined recurrence rate in the expansile and infiltrative MOC was 6.9% (95%CI: 3.1-11.9) and 24.5% (95%CI: 14.3-36.2). The combined International Federation of Gynecology and Obstetrics (FIGO) I rate in the expansile and infiltrative MOC was 89.8% (95%CI: 84.9-94.0) and 56.2% (95%CI: 41.5-70.4). A significant association was found between tumor type and FIGO stage (χ² (3) = 110.92, p < 0.00001).
Conclusion:
Expansile MOC predicts better outcomes, while infiltrative MOC is linked to advanced stages and poorer prognosis. Complete surgical staging is crucial for infiltrative MOC but optional for early-stage expansile MOC. Early-stage patients should consider fertility-sparing surgery, timely conception, and close recurrence monitoring.

