The annual recurrence risk model for tailored surveillance strategy in patients with cervical cancer

Purpose: Current guidelines for surveillance strategy in cervical cancer are rigid, recommending the same strategy for all survivors. The aim of this study was to develop a robust model allowing for individualised surveillance based on a patient's risk profile. Methods: Data of 4343 early-stage patients with cervical cancer treated between 2007 and 2016 were obtained from the international SCCAN (Surveillance in Cervical Cancer) consortium. The Cox proportional hazards model predicting disease-free survival (DFS) was developed and internally validated. The risk score, derived from regression coefficients of the model, stratified the cohort into significantly distinctive risk groups. On its basis, the annual recurrence risk model (ARRM) was calculated. Results: Five variables were included in the prognostic model: maximal pathologic tumour diameter; tumour histotype; grade; number of positive pelvic lymph nodes; and lymphovascular space invasion. Five risk groups significantly differing in prognosis were identified with a five-year DFS of 97.5%, 94.7%, 85.2% and 63.3% in increasing risk groups, whereas a two-year DFS in the highest risk group equalled 15.4%. Based on the ARRM, the annual recurrence risk in the lowest risk group was below 1% since the beginning of follow-up and declined below 1% at years three, four and >5 in the medium-risk groups. In the whole cohort, 26% of recurrences appeared at the first year of the follow-up, 48% by year two and 78% by year five. Conclusion: The ARRM represents a potent tool for tailoring the surveillance strategy in early-stage patients with cervical cancer based on the patient's risk status and respective annual recurrence risk. It can easily be used in routine clinical settings internationally

Post-recurrence survival in patients with cervical cancer.

BACKGROUND: Up to 26% of patients with early-stage cervical cancer experience relapse after primary surgery. However, little is known about which factors influence prognosis following disease recurrence. Therefore, our aims were to determine post-recurrence disease-specific survival (PR-DSS) and to identify respective prognostic factors for PR-DSS. METHODS: Data from 528 patients with early-stage cervical cancer who relapsed after primary surgery performed between 2007 and 2016 were obtained from the SCANN study (Surveillance in Cervical CANcer). Factors related to the primary disease and recurrence were combined in a multivariable Cox proportional hazards model to predict PR-DSS. RESULTS: The 5-year PR-DSS was 39.1% (95% confidence interval [CI] 22.7%-44.5%), median disease-free interval between primary surgery and recurrence (DFI1) was 1.5 years, and median survival after recurrence was 2.5 years. Six significant variables were identified in the multivariable analysis and were used to construct the prognostic model. Two were related to primary treatment (largest tumour size and lymphovascular space invasion) and four to recurrence (DFI1, age at recurrence, presence of symptoms, and recurrence type). The C-statistic after 10-fold cross-validation of prognostic model reached 0.701 (95% CI 0.675-0.727). Three risk-groups with significantly differing prognoses were identified, with 5-year PR-DSS rates of 81.8%, 44.6%, and 12.7%. CONCLUSIONS: We developed the robust model of PR-DSS to stratify patients with relapsed cervical cancer according to risk profiles using six routinely recorded prognostic markers. The model can be utilised in clinical practice to aid decision-making on the strategy of recurrence management, and to better inform the patients

The annual recurrence risk model for tailored surveillance strategy in patients with cervical cancer

Purpose: Current guidelines for surveillance strategy in cervical cancer are rigid, recommending the same strategy for all survivors. The aim of this study was to develop a robust model allowing for individualised surveillance based on a patient's risk profile. Methods: Data of 4343 early-stage patients with cervical cancer treated between 2007 and 2016 were obtained from the international SCCAN (Surveillance in Cervical Cancer) consortium. The Cox proportional hazards model predicting disease-free survival (DFS) was developed and internally validated. The risk score, derived from regression coefficients of the model, stratified the cohort into significantly distinctive risk groups. On its basis, the annual recurrence risk model (ARRM) was calculated. Results: Five variables were included in the prognostic model: maximal pathologic tumour diameter; tumour histotype; grade; number of positive pelvic lymph nodes; and lymphovascular space invasion. Five risk groups significantly differing in prognosis were identified with a five-year DFS of 97.5%, 94.7%, 85.2% and 63.3% in increasing risk groups, whereas a two-year DFS in the highest risk group equalled 15.4%. Based on the ARRM, the annual recurrence risk in the lowest risk group was below 1% since the beginning of follow-up and declined below 1% at years three, four and >5 in the medium-risk groups. In the whole cohort, 26% of recurrences appeared at the first year of the follow-up, 48% by year two and 78% by year five. Conclusion: The ARRM represents a potent tool for tailoring the surveillance strategy in early-stage patients with cervical cancer based on the patient's risk status and respective annual recurrence risk. It can easily be used in routine clinical settings internationally