Abstract
Aims
To develop a new package of joint model to fit longitudinal CA125 in epithelial ovarian cancer relapse.
Patients & methods
Included were 305 epithelial ovarian cancer patients who reached complete remission after cytoreductive surgery and first-line chemotherapy. Univariate and multivariate analysis with a joint model was performed to select independent risk factors, which were subsequently combined to predict recurrence.
Results
Independent factors were longitudinal CA125, age, stage and residual tumor size (p < 0.05). Prediction of recurrence with these factors had an average of 80.7% accuracy, 5.6–10.7% better than kinetic factors.
Conclusion
The new package of joint model fits longitudinal CA125 well. Potential application can be extended to other biomarkers.
Acknowledgements
The authors are grateful to Yu-Che Chung for his help with statistical algorithms.
Financial & competing interests disclosure
The study was supported in part by a grant from the National Science Council of Taiwan (NSC 102-2118-M-110-003) and a grant from Kaohsiung Veterans’ General Hospital (VGHKS 102-071). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.
No writing assistance was utilized in the production of this manuscript.
Ethical conduct of research
The authors state that they have obtained appropriate institutional review board approval or have followed the principles outlined in the Declaration of Helsinki for all human or animal experimental investigations. In addition, for investigations involving human subjects, informed consent has been obtained from the participants involved.