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  • Clinical characteristics an...
    Li, Xiaofen; Zhang, Wei; Ding, Peirong; Guo, Rui; Hong, Zhigang; Liu, Peng; Wang, Ziqiang; Yu, Yongyang; Fang, Chao; Meng, Wenjian; Zhang, Rui; Qiu, Meng

    International journal of colorectal disease, 06/2021, Volume: 36, Issue: 6
    Journal Article

    Purpose As a kind of secondary tumor of the ovary, ovarian metastasis from colorectal cancer (OMCRC) happens rarely. Prognostic factors of OMCRC are still undetermined. This study was conducted to analyze clinical characteristics and prognostic factors of OMCRC patients. Methods Data of patients with OMCRC were collected retrospectively from four large-capacity hospitals in China. Kaplan-Meier method was applied to estimate disease-specific overall survival (OS), and multivariate Cox regression analysis was used to identify prognostic factors. A novel nomogram was developed to estimate individual survival probability, whose performance was internally validated using concordance index (C-index) and calibration curve. Results Totally, 162 cases were eligible, with a median age at diagnosis of 49 years old. The median size of ovarian metastases was 9.0 cm (95% CI: 8.5–10.4 cm). 93.8% of patients received surgery of ovarian metastases. Median time from CRC diagnosis to metachronous ovarian metastasis was 13.0 months (95% CI: 13.5–17.7 months). Median OS after ovarian metastasis diagnosis was 26.0 months (95% CI: 22.3–29.7 months). Integrating univariate and multivariate analyses, eight factors (including age, menopausal status, primary tumor location, N stage of primary tumor, surgery of primary tumor, differentiation grade, bilateral metastasis, and systemic chemotherapy) were used to develop a novel nomogram, with a C-index of 0.65 (95% CI: 0.595–0.705). Calibration curves indicated relatively good agreement between predicted and actual survival. Conclusions This nomogram could be a promising tool to help clinicians to estimate individual survival outcome of patients with OMCRC. Further study is warranted to validate the practicality of this model.