Validation of a nomogram for predicting outcome of vulvar cancer patients, primarily treated by surgery, in Korean population: multicenter retrospective study through Korean Gynecologic Oncology Group (KGOG-1010)

Abstract

Objective: Regarding vulvar cancer, a nomogram has been suggested for the prediction of relapse-free survival (RFS). While the nomogram has been developed and validated in a Western study, there was no validation in Korean population. Thus, we have undertaken the study to assess the applicability of nomogram for predicting RFS in Korean patients with vulvar cancer. Methods: A total of 204 cases newly diagnosed as vulvar cancer between 1982 and 2006 were identified. Among them 70 cases were not eligible due to inappropriate cell type (40 cases) and radiation as primary therapy (30 cases). Fortyfour cases were not evaluable due to inadequate data and persistent disease. Finally a total of 90 patients primarily treated by surgery were included for analysis. Variables including age and the characteristics of primary tumor, nodal status, and surgical margin were collected for predicting RFS based on nomogram, which was compared with actual RFS. A calibration plot was drawn showing the actual versus predicted probability for 6 groups of patients segregated according to their predicted probabilities. In addition, discrimination of the nomogram was quantified with the concordance index. Results: Patients' mean age was 58 years and mean follow-up period was 47.9 months. Observed 2y-and 5y-RFS rates were 81% and 68%, respectively, corresponding to 79% and 72% in the original cohort. The trend line in calibration plot showed comparable concordance with an ideal line, having a slope of 1.04 for 2y-RFS (R 2 =.35) and 0.98 for 5y-RFS (R 2 =.80), respectively. The concordance index was 0.79 in the KGOG data set, which was improved to 0.82 with the data set limited to squamous cell carcinoma. Conclusion:The nomogram provides the predictive capacity for relapse-free survival in Korean patients with vulvar cancer.

Developing and Validating Novel Nomograms for Predicting the Overall Survival and Cancer-Specific Survival of Patients With Primary Vulvar Squamous Cell Cancer

“…In line with previous studies, our model comprises age, tumor size, pathologic grade, radiotherapy, chemotherapy, surgery, and M stage, which were significant factors associated with CSS and included in the previously generated nomograms ( 9 , 10 , 14 ). Moreover, the FIGO stage was not included in our final model, although it was the most prevalent stage system for gynecological cancers, similar to two studies ( 9 , 10 ).…”

“…Nomograms for predicting the cancer-specific survival (CSS) of the patients with VC have been developed. For example, a nomogram based on age, American Joint Committee on Cancer (AJCC) T stage, invasion depth, margin status, and lymph nodes status had a Harrell's C concordance statistics (C-statistic) of 0.78 and 0.83 in the validation study and training study, respectively ( 9 , 10 ). However, detection of margin status and the number of lymph nodes involved are difficult and highly influenced by the experience and imaging techniques of clinicians.…”

Condyloma-like squamous cell carcinoma of the vulva: report of two midline cases

“…The 5-year survival rates for vulvar SCC have been estimated as 41% for India, 18 68% for South Korea, 19 and 86% in the United States. 1 The most important negative prognostic factor for vulvar SCC is the inguinofemoral lymph node status at the time of initial diagnosis.…”

Nomograms to predict isolated loco-regional or distant recurrence among women with uterine cancer

“…To estimate such risk, nomograms have been developed and used for a variety of cancers in the past. Nomograms are graphical tools that represent a complex mathematical or statistical equation in a simplified way and have been developed for nongynaecological [7][8][9][10][11][12][13][14] and for gynaecological [15][16][17][18] cancers. Nomograms assist clinicians to estimate an individual patient's risk of recurrence, prognosis, individualize treatment and assist with the selection of patients for randomized clinical trials.…”