Analysis of Recurrent Events with Associated Informative Censoring: Application to HIV Data
DOI:
https://doi.org/10.6000/1929-6029.2020.09.03Keywords:
Recurrent events, Loss to follow-up, HIV, Prentice, Williams and Peterson Gap-Time, Informative censoringAbstract
In this study, we adapt a Cox-based model for recurrent events; the Prentice, Williams and Peterson Total -Time (PWP-TT) that has largely, been used under the assumption of non-informative censoring and evaluate it under an informative censoring setting. Empirical evaluation was undertaken with the aid of the semi-parametric framework for recurrent events suggested by Huang [1] and implemented in R Studio software. For validation we used data from a typical HIV care setting in Kenya. Of the three models under consideration; the standard Cox Model had gender hazard ratio (HR) of 0.66 (p-value=0.165), Andersen-Gill had HR 0.46 (with borderline p-value=0.054) and extended PWP TT had HR 0.22 (p-value=0.006). The PWP-TT model performed better as compared to other models under informative setting. In terms of risk factors under informative setting, LTFU due to stigma; gender [base=Male] had HR 0.544 (p-value =0.002), age [base is < 37] had HR 0.772 (p-value=0.008), ART regimen [base= First line] had HR 0.518 (p-value= 0.233) and differentiated care model (Base=not on DCM) had HR 0.77(p-value=0.036). In conclusion, in spite of the multiple interventions designed to address incidences of LTFU among HIV patients, within-person cases of LTFU are usually common and recurrent in nature, with the present likelihood of a person getting LTFU influenced by previous occurrences and therefore informative censoring should be checked
References
Huang C-Y, Wang M-C. Joint Modeling and Estimation for Recurrent Event Processes and Failure Time Data. J Am Stat Assoc 2004;99(468):1153-65. https://doi.org/10.1198/016214504000001033 DOI: https://doi.org/10.1198/016214504000001033
Chiou SH [Steven], Huang C-Y. reReg: Recurrent Event Regression [Internet]. 2018 [cited 2019 Jul 23]. Available from: https://CRAN.R-project.org/package=reReg
Lawless JF. Regression Methods for Poisson Process Data. J Am Stat Assoc 1987;82(399):808-15. https://doi.org/10.1080/01621459.1987.10478502 DOI: https://doi.org/10.1080/01621459.1987.10478502
Kelly PJ, Lim LL-Y. Survival analysis for recurrent event data: an application to childhood infectious diseases. Stat Med 2000;19(1):13-33. https://doi.org/10.1002/(SICI)1097-0258(20000115)19:1<13::AID-SIM279>3.0.CO;2-5 DOI: https://doi.org/10.1002/(SICI)1097-0258(20000115)19:1<13::AID-SIM279>3.0.CO;2-5
Yang W, Jepson C, Xie D, Roy JA, Shou H, Hsu JY, et al. Statistical Methods for Recurrent Event Analysis in Cohort Studies of CKD. Clin J Am Soc Nephrol 2017;12(12):2066-73. https://doi.org/10.2215/CJN.12841216 DOI: https://doi.org/10.2215/CJN.12841216
Andersen PK, Gill RD. Cox’s Regression Model for Counting Processes: A Large Sample Study. Ann Stat 1982;10(4):1100-20. https://doi.org/10.1214/aos/1176345976 DOI: https://doi.org/10.1214/aos/1176345976
Prentice RL, Williams BJ, Peterson AV. On the regression analysis of multivariate failure time data. Biometrika 1981;68(2):373-9. https://doi.org/10.1093/biomet/68.2.373 DOI: https://doi.org/10.1093/biomet/68.2.373
Wei LJ, Lin DY, Weissfeld L. Regression Analysis of Multivariate Incomplete Failure Time Data by Modeling Marginal Distributions. J Am Stat Assoc 1989;84(408):1065-73. https://doi.org/10.1080/01621459.1989.10478873 DOI: https://doi.org/10.1080/01621459.1989.10478873
Ghosh D, Lin DY. Semiparametric Analysis of Recurrent Events Data in the Presence of Dependent Censoring. Biometrics 2003;59(4):877-85. https://doi.org/10.1111/j.0006-341X.2003.00102.x DOI: https://doi.org/10.1111/j.0006-341X.2003.00102.x
Christel Castelli, Philippe Saint-Pierre, Jean-Pierre Daures. Informative censoring in survival analysis and application to asthma | Christel Castelli | Request PDF [Internet]. ResearchGate. 2006 [cited 2019 Jul 22]. Available from: https://www.researchgate.net/publication/262413091_Informative_censoring_in_survival_analysis_and_application_to_asthma/citations
Lin DY, Wei LJ, Ying Z. Accelerated Failure Time Models for Counting Processes. Biometrika 1998;85(3):605-18. https://doi.org/10.1093/biomet/85.3.605 DOI: https://doi.org/10.1093/biomet/85.3.605
Berheto TM, Haile DB, Mohammed S. Predictors of Loss to follow-up in Patients Living with HIV/AIDS after Initiation of Antiretroviral Therapy. North Am J Med Sci 2014;6(9):453-9. https://doi.org/10.4103/1947-2714.141636 DOI: https://doi.org/10.4103/1947-2714.141636
Assemie MA, Muchie KF, Ayele TA. Incidence and predictors of loss to follow up among HIV-infected adults at Pawi General Hospital, northwest Ethiopia: competing risk regression model. BMC Res Notes [Internet]. 2018 May 10 [cited 2019 Jul 4];11. https://doi.org/10.1186/s13104-018-3407-5 DOI: https://doi.org/10.1186/s13104-018-3407-5
Amorim LD, Cai J. Modelling recurrent events: a tutorial for analysis in epidemiology. Int J Epidemiol 2015;44(1):324-33. https://doi.org/10.1093/ije/dyu222 DOI: https://doi.org/10.1093/ije/dyu222
Therneau TM, Grambsch PM. Modeling Survival Data: Extending the Cox Model. Springer Science & Business Media 2000;p. 372. https://doi.org/10.1007/978-1-4757-3294-8 DOI: https://doi.org/10.1007/978-1-4757-3294-8
Ullah S, Gabbett TJ, Finch CF. Statistical modelling for recurrent events: an application to sports injuries. Br J Sports Med 2014;48(17):1287-93. https://doi.org/10.1136/bjsports-2011-090803 DOI: https://doi.org/10.1136/bjsports-2011-090803
Odhiambo C, Odhiambo J, Omolo B. A Smooth Test of Goodness-of-Fit for the Baseline Hazard Function for Time-to-First Occurrence in Recurrent Events: An Application to HIV Retention Data. Int J Stat Med Res 2017;6(3):104-113. https://doi.org/10.6000/1929-6029.2017.06.03.2 DOI: https://doi.org/10.6000/1929-6029.2017.06.03.2
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Policy for Journals/Articles with Open Access
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are permitted and encouraged to post links to their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work
Policy for Journals / Manuscript with Paid Access
Authors who publish with this journal agree to the following terms:
- Publisher retain copyright .
- Authors are permitted and encouraged to post links to their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work .
