A Nomogram for Predicting Progression-free Survival in Patients with Endometrial Cancer |
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| Institution: | 1. Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan, China;2. Department of Ultrasound, Shandong Provincial Hospital affiliated to Shandong First Medical University, Jinan, China;3. Department of Obstetrics and Gynecology, Weifang People''s Hospital, Weifang, China;1. Department of Oncology, University of Ostrava, Ostrava, Czech Republic;2. Northumbria Healthcare NHS Trust, Newcastle upon Tyne, UK;3. Northern Centre for Cancer Care, Freeman Hospital, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK;4. Institute of Dentistry and Oral Sciences, Palacky University Olomouc, Olomouc, Czech Republic;5. Department of Oral and Maxillofacial Surgery, Royal Sunderland Hospital, Sunderland, UK;1. Department of Radiation Oncology, Bioinformatics and Biostatistics, Moffitt Cancer Center, Tampa, Florida, USA;2. College of Medicine, University of South Florida, Tampa, Florida, USA;3. Department of Radiation Oncology, Cleveland Clinic, Cleveland, Ohio, USA;4. Translational Hematology and Oncology Research, Cleveland Clinic, Cleveland, Ohio, USA;5. School of Medicine Western Reserve University, Cleveland, Ohio, USA;1. Department of Radiation Oncology, RMLIMS, Lucknow, India;2. Department of Radiation Oncology, KGMU, Lucknow, India;1. Clinical Effectiveness Unit, The Royal College of Surgeons of England, London, UK;2. Department of Health Services Research & Policy, London School of Hygiene & Tropical Medicine, London, UK;3. National Cancer Registration and Analysis Service, NHS Digital, Birmingham, UK;4. Nuffield Department of Population Health, University of Oxford, Oxford, UK;5. Department of Breast Surgery, St James''s University Hospital, Leeds, UK;1. Department of Radiology, Medanta Hospital Gurgaon, India;2. Medanta Institute of Gastroenterology and Hepatobiliary Sciences, Medanta Hospital Gurgaon, India;3. Medanta Institute of Medical and Radiation Oncology, Medanta Hospital Gurgaon, India;4. Department of Pathology, Medanta Hospital Gurgaon, India |
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| Abstract: | AimsEndometrial cancer is one of the most widely known gynaecological malignancies that lacks a prognostic prediction model. This study aimed to develop a nomogram to predict progression-free survival (PFS) in patients with endometrial cancer.Materials and methodsInformation for endometrial cancer patients diagnosed and treated from 1 January 2005 to 30 June 2018 was collected. The Kaplan–Meier survival analysis and multivariate Cox regression analysis were carried out to determine the independent risk factors and a nomogram was constructed by R based on analytical factors. Internal and external validation were then carried out to predict the probability of 3- and 5-year PFS.ResultsIn total, 1020 patients with endometrial cancer were included in the study and the relationship between 25 factors and prognosis was analysed. Postmenopause (hazard ratio = 2.476, 95% confidence interval 1.023–5.994), lymph node metastasis (hazard ratio = 6.242, 95% confidence interval 2.815–13.843), lymphovascular space invasion (hazard ratio = 4.263, 95% confidence interval 1.802–10.087), histological type (hazard ratio = 2.713, 95% confidence interval 1.374–5.356), histological differentiation (hazard ratio = 2.601, 95% confidence interval 1.141–5.927) and parametrial involvement (hazard ratio = 3.596, 95% confidence interval 1.622–7.973) were found to be independent prognostic risk factors; these factors were selected to establish a nomogram. The consistency index for 3-year PFS were 0.88 (95% confidence interval 0.81–0.95) in the training cohort and 0.93 (95% confidence interval 0.87–0.99) in the verification set. The areas under the receiver operating characteristic curve for the 3- and 5-year PFS predictions are 0.891 and 0.842 in the training set; the same conclusion also appeared in the verification set 0.835 (3-year), 0.803(5-year)].ConclusionsThis study established a prognostic nomogram for endometrial cancer that provides a more individualised and accurate estimation of PFS for patients, which will help physicians make follow-up strategies and risk stratification. |
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| Keywords: | Endometrial neoplasms nomograms prognosis progression-free survival |
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