Abstract
OBJECTIVE: Stage I-II uterine papillary serous carcinoma (UPSC) has aggressive biological behavior and leads to poor prognosis. However, clinicopathologic risk factors to predict cancer-specific survival of patients with stage I-II UPSC were still unclear. This study was undertaken to develop a prediction model of survival in patients with early-stage UPSC. METHODS: Using Surveillance, Epidemiology, and End Results (SEER) database, 964 patients were identified with International Federation of Gynecology and Obstetrics (FIGO) stage I-II UPSC who underwent at least hysterectomy between 2004 and 2015. By considering competing risk events for survival outcomes, we used proportional subdistribution hazards regression to compare cancer-specific death (CSD) for all patients. Based on the results of univariate and multivariate analysis, the variables were selected to construct a predictive model; and the prediction results of the model were visualized using a nomogram to predict the cancer-specific survival and the response to adjuvant chemotherapy and radiotherapy of stage I-II UPSC patients. RESULTS: The median age of the cohort was 67 years. One hundred and sixty five patients (17.1%) died of UPSC (CSD), while 8.6% of the patients died from other causes (non-CSD). On multivariate analysis, age ≥ 67 (HR = 1.45, P = .021), tumor size ≥ 2 cm (HR = 1.81, P = .014) and >10 regional nodes removed (HR = 0.52, P = .002) were significantly associated with cumulative incidence of CSD. In the age ≥67 cohort, FIGO stage IB-II was a risk factor for CSD (HR = 1.83, P = .036), and >10 lymph nodes removed was a protective factor (HR = 0.50, P = .01). Both adjuvant chemotherapy combined with radiotherapy and adjuvant chemotherapy alone decreased CSD of patients with stage I-II UPSC older than 67 years (HR = 0.47, P = .022; HR = 0.52, P = .024, respectively). The prediction model had great risk stratification ability as the high-risk group had higher cumulative incidence of CSD than the low-risk group (P < .001). In the high-risk group, patients with post-operative adjuvant chemoradiotherapy had improved CSD compared with patients who did not receive radiotherapy nor chemotherapy (P = .037). However, there was no such benefit in the low-risk group. CONCLUSION: Our prediction model of CSD based on proportional subdistribution hazards regression showed a good performance in predicting the cancer-specific survival of early-stage UPSC patients and contributed to guide clinical treatment decision, helping oncologists and patients with early-stage UPSC to decide whether to choose adjuvant therapy or not.