Zhang S, Liu X, Li Q, Pan Y, Tian Y, Gu X. Nomogram incorporating log odds of positive lymph nodes improves prognostic prediction for ovarian serous carcinoma: a real-world retrospective cohort study.
BMJ Open 2023;
13:e074206. [PMID:
37865413 PMCID:
PMC10603516 DOI:
10.1136/bmjopen-2023-074206]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 09/28/2023] [Indexed: 10/23/2023] Open
Abstract
OBJECTIVES
Ovarian serous carcinoma (OSC) is a major cause of gynaecological cancer death, yet there is a lack of reliable prognostic models. To address this, we developed and validated a nomogram based on conventional clinical characteristics and log odds of positive lymph nodes (LODDS) to predict the prognosis of OSC patients.
SETTING
A Real-World Retrospective Cohort Study from the Surveillance, Epidemiology and End Results programme.
PARTICIPANTS
We obtained data on 4192 patients diagnosed with OSC between 2010 and 2015. Eligibility criteria included specific diagnostic codes, OSC being the primary malignant tumour and age at diagnosis over 18 years. Exclusion criteria were missing information on various factors and unknown cause of death or survival time.
PRIMARY AND SECONDARY OUTCOME MEASURES
The primary outcome were overall survival (OS) and ovarian cancer-specific survival (OCSS).
RESULTS
For OS and OCSS outcomes, we selected 7 and 5 variables, respectively, to establish the nomogram. In the training and validation cohorts, the C index for OS or OCSS was 0.716 or 0.718 and 0.731 or 0.733, respectively, with a 3-year time-dependent area under the curve (AUC) of 0.745 or 0.751 and a 5-year time-dependent AUC of 0.742 or 0.751. Calibration curves demonstrated excellent consistency between predicted and observed outcomes. The Net Reclassification Index, integrated discrimination improvement and decision curve analysis curves indicated that our nomogram performed better than the International Federation of Gynaecology and Obstetrics (FIGO) staging system in predicting OS and OCSS for OSC patients in both the training and validation cohorts.
CONCLUSION
Our nomogram, which includes LODDS, offers higher accuracy and reliability than the FIGO staging system and can predict overall and OCSS in OSC patients.
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