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A gap time model based on a multiplicative marginal rate function that accounts for zero-recurrence units.

Francisco Louzada1, Márcia Ac Macera1, Vicente G Cancho1

  • 1Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo, Brazil.

Statistical Methods in Medical Research
|May 11, 2017
PubMed
Summary

This study introduces a new recurrent event data model that equally treats gap times, simplifying analysis. The model effectively analyzes hospital readmission data for colorectal cancer patients.

Keywords:
Poisson processRecurrent eventsWeibull distributiongap timelong-term survival modelszero-recurrence

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Area of Science:

  • Biostatistics
  • Survival Analysis
  • Health Services Research

Background:

  • Recurrent event data analysis presents challenges in modeling the relationship between successive event times.
  • Existing models may not adequately account for individuals who never experience the event of interest (zero-recurrence units).

Purpose of the Study:

  • To propose an alternative gap time model for recurrent event data.
  • To incorporate a proportion of zero-recurrence units into the recurrent event data model.
  • To apply the novel model to hospital readmission data in colorectal cancer patients.

Main Methods:

  • Developed a gap time model using a multiplicative marginal rate function.
  • Formulated gap times conditional on previous recurrence times, treating them equally.
  • Employed maximum likelihood estimation for model inference and conducted simulation studies.

Main Results:

  • The proposed model simplifies the analysis of successive events by treating gap times equally.
  • The model demonstrated good performance in simulation studies for the estimation procedure.
  • The model was successfully applied to real-world hospital readmission data.

Conclusions:

  • The alternative gap time model provides a flexible and effective approach for analyzing recurrent event data.
  • The inclusion of zero-recurrence units enhances the model's applicability to diverse datasets.
  • The model shows promise for analyzing patient readmission data and similar health-related events.