Ethical approval was obtained from the institutional review board of Sun Yat-sen University Cancer Centre. The need for informed consent was waived since no identifiable information was used in this study.
An evaluation of the institutional database for medical records from January 1994 to December 2014 was performed to identify patients with ovarian cancer who received initial treatment at the Sun Yat-sen University Cancer Centre. Only patients who met the following criteria were included in the study: newly diagnosed, histologically confirmed epithelial ovarian cancer; stage II-IV disease; serially measured CA125 levels; and complete follow-up data. In total, 1740 patients were identified; 491 patients who met the above-mentioned inclusion criteria were included as the primary cohort (the training cohort).
The clinicopathologic data were extracted, including age, neutrophil-to-lymphocyte ratio, platelet count, serum albumin level, International Federation of Gynecology and Obstetrics (FIGO) stage, histologic type, tumor grade, diameter of residual disease, CA125 levels after three cycles of chemotherapy (normal CA125 levels were defined as being ≤ 35 U/mL), follow-up, recurrence and vital status.
The standard treatment for advanced ovarian cancer in our institution comprised comprehensive staging or primary debulking surgery followed by adjuvant chemotherapy. Neoadjuvant chemotherapy followed by interval debulking surgery was performed in patients with bulky stage III/IV disease who were not eligible surgical candidates. Surgery mainly included total hysterectomy, bilateral salpingo-oophorectomy, omentectomy, lymphadenectomy, and resection of all visible bulky tumor. Bowel resection, splenectomy, and partial liver resection were performed as warranted to remove all macroscopic tumor. Residual disease < 1 cm in maximum diameter after surgery was defined as optimal debulking, whereas residual disease ≥ 1 cm was considered suboptimal debulking. Adjuvant chemotherapy mainly included ≥ 6 cycles of platinum-based systemic chemotherapy.
Patients were followed up periodically after primary treatment. Monitoring comprised pelvic examination, abdominal and pelvic ultrasonography, and examination of the levels of CA125 and other tumor markers every 3 months for 3 years, then every 6 months for 2 years, and annually after 5 years. Computed tomography (CT), magnetic resonance imaging (MRI), or positron emission tomography- computed tomography (PET-CT) were performed if clinically indicated.
All procedures were carried out in accordance with the approved guidelines of our institute.
An external validation cohort was screened from patients with ovarian cancer who received initial treatment at other hospitals between January 2001 and August 2016 using the same criteria as the primary cohort. Most of these patients were transferred to our institution because of disease recurrence, and the rest who did not experience recurrence came to our institution for follow-up. It should be noted that only the medical records of initial treatment of these patients at other hospitals were used in this study, which guaranteed these patients as an independent validation cohort. However, the vital status for the external validation cohort was ascertained by reviewing their final medical records at our institution.
Construction of the Nomogram
PFS was defined as the interval between the date of diagnosis and the date of first recurrence or death, or the date of last contact for living patients without recurrent disease. In the primary cohort, PFS according to different variables was estimated using the Kaplan-Meier method and compared using the log-rank test. Multivariate Cox proportional hazards regression analysis was used to identify the independent prognostic factors. We established the nomogram in the primary cohort (training cohort) by incorporating the significant prognostic factors into the Cox regression model using the “rms” package in R software.
Performance of the Nomogram in the Primary Cohort
The Harrell’s concordance index (C-index) was calculated to estimate the discrimination ability of the nomogram. The nomogram was subjected to 1000 bootstrap resamples for internal validation. The value of the C-index ranges from 0.5 to 1.0, with 0.5 indicating random chance and 1.0 indicating perfectly corrected discrimination. Calibration plots, which showed the consistency between the outcomes predicted by the nomogram and actual outcomes, were used to assess the robustness of the model.
External Validation of the Nomogram
The nomogram was applied to the external validation cohort for external validation. Using the same methods as in the primary cohort, discrimination and model calibration were tested.
Incremental Predictive Value of CA125 Levels to the Nomogram
We investigated the incremental predictive value of the normalization of CA125 levels after three cycles of chemotherapy to the nomogram by comparing the respective C-index for the model with and without CA125 levels after three cycles of chemotherapy.
Comparison of the Nomogram with the FIGO Staging System in Discrimination Ability
Furthermore, we attempted to demonstrate the superiority in discrimination ability of the established nomogram over the FIGO staging system. First, the nomogram and the FIGO staging system were compared with respect to the C-index. Next, patients in the primary cohort were classified into low, moderate, and high risk groups by ranking their nomogram calculated scores into tertiles. The distributions of the PFS for these risk groups, as well as for different FIGO stages, were depicted by the Kaplan–Meier method and analyzed by the log-rank test.
Decision curve analysis (DCA) was performed to examine the clinical application of the nomogram by quantifying the net benefits at different threshold probabilities in the primary cohort.[16, 17] In addition, DCA was also conducted for the model that did not integrate CA125 levels after three cycles of chemotherapy.
Statistical analysis was performed using R version 3.5.1 and SAS version 9.3 (SAS Institute Inc. Cary, NC, USA). P values less than 0.05 were considered statistically significant. All tests were two-sided. Details of R code and SAS codes for running nomograms were shown in Appendix 1.
The key raw data have been recorded at Sun Yat-sen University Cancer Center for future reference (number RDDA 2019000972).