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960 The annual recurrence risk model for tailored surveillance strategy in cervical cancer patients
  1. D Cibula1;2,
  2. J Jarkovsky3,
  3. L Van Lonkhuijzen4,
  4. H Falconer5,
  5. A Fagotti6,
  6. A Ayhan7,
  7. S Kim8,
  8. D Isla Ortiz9,
  9. J Klat10,
  10. A Obermair11,
  11. F Landoni12,
  12. J Rodriguez13,
  13. R Manchanda14,
  14. J Kostun15,
  15. R Dos Reis16,
  16. MM Meydanli17,
  17. D Odetto18,
  18. R Laky19,
  19. M Borčinová1;2 and
  20. A Lopez20
  1. 1First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic, Gynecologic Oncology Center, Department of Obstetrics and Gynecology, Prague, Czech Republic
  2. 2Central and Eastern European Gynecologic Oncology Group, CEEGOG, Prague, Czech Republic
  3. 3Institute of Biostatistics and Analyses, Faculty of Medicine, Masaryk University, Brno, Czech Republic
  4. 4Amsterdam UMC, locatie AMC, Gynecologic Oncology, Amsterdam, Netherlands
  5. 5Karolinska University Hospital and Department of Women’s and Children’s Health, Karolinska Institutet, Department of Pelvic Cancer, Stockholm, Sweden
  6. 6Fondazione Policlinico Universitario A. Gemelli, IRCCS, UOC Ginecologia Oncologica, Dipartimento per la salute della Donna e del Bambino e della Salute Pubblica, Roma, Italy
  7. 7Baskent University School of Medicine Department of Gynecology and Obstetrics Division of Gynecologic Oncology, Ankara, Turkey
  8. 8Memorial Sloan Kettering Cancer Center, Department of Surgery, New York, USA
  9. 9Gynecology Oncology Center, National Institute of Cancerology Mexico, Mexico, Mexico
  10. 10Faculty of Medicine, University Hospital and University of Ostrava, Department of Obstetrics and Gynecology, Ostrava, Czech Republic
  11. 11Queensland Centre for Gynaecological Cancer, The University of Queensland, Australia
  12. 12University of Milano-Bicocca, Department of Obstetrics and Gynecology, Gynaecologic Oncology Surgical Unit, ASST-Monza, San Gerardo Hospital, Monza, Italy
  13. 13Instituto Nacional de Cancerología, in Bogotá, Department of Gynecologic Oncology, Bogota, Colombia
  14. 14Wolfson Institute of Preventive Medicine, Barts Cancer Centre, Queen Mary University of London, and Barts Health NHS Trust, London, UK
  15. 15University Hospital Pilsen, Charles University in Prague, Department of Gynaecology and Obstetrics, Czech Republic
  16. 16The University of Texas MD Anderson Cancer Center, Department of Gynecologic Oncology and Reproductive Medicine, Houston, USA
  17. 17Zekai Tahir Burak Women‘s Health and Research Hospital, University of Health Sciences, Department of Gynecologic Oncology, Ankara, Turkey
  18. 18Hospital Italiano de Buenos Aires, Instituto Universitario Hospital Italiano, Department of Gynecologic Oncology, Buenos Aires, Argentina
  19. 19Medical University of Graz, Gynecology, Graz, Austria
  20. 20National Institute of Neoplastic Diseases, Department of Gynecological Surgery, Lima, Peru


Introduction/Background*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 and comprehensive model allowing for individualised surveillance strategy based on risk profile of early-stage cervical cancer patients that were referred for surgical treatment with curative intent.

Methodology The data of 4,343 cervical cancer patients with pathologically confirmed early-stage cervical cancer treated between 2007 and 2016 were obtained from SCANN consortium centres of excellence (Surveillance in Cervical CANcer). Only patients with complete key predictor variables and a minimum of one-year follow-up data availability were included. Based on the prognostic markers, a multivariable Cox proportional hazards model predicting disease-free survival (DFS) was developed and internally validated. A 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 by conditional survival analysis.

Result(s)*Five variables significant in multivariable analysis of recurrence risk were included in the prognostic model: maximal pathologic tumour diameter, tumour histotype, tumour grade, the number of positive pelvic lymph nodes, and lymphovascular space invasion (table 1). The model was ten-fold internally cross-validated with the average AUC of 0.732. Five risk groups significantly differing in prognosis were identified: with five-year DFS of 97.5%, 94.7%, 85.2%, and 63.3% in consecutive increasing risk groups, while two-year DFS in the highest risk group equalled 15.4%. Based on ARRM, the annual recurrence risk in the lowest risk group was below 1% in the first year of follow-up and declined below 1% at years three, four, and >5 in the three medium-risk groups (figure 1). The proportion of pelvic recurrences declined in groups with the growing risk. 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.

Abstract 960 Table 1

Multivariate model for risk of recurrence prediction

Abstract 960 Figure 1

ARRM: Landmark analysis of the annual probability of recurrence after surgery. N/A not analysed.

Conclusion*ARRM represents a powerful tool for tailoring the surveillance strategy in early-stage cervical cancer patients based on the patient´s risk status and respective annual recurrence risk. It can easily be utilised in routine clinical settings internationally.

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