Comparison of Cox proportional hazards model, Cox proportional hazards with time-varying coefficients model, and lognormal accelerated failure time model: Application in time to event analysis of melioidosis patients

Kamaruddin Mardhiah; Kamaruddin Mardhiah; Nadiah Wan-arfah; Nyi Naing; Muhammad Hassan; Huan-keat Chan

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Comparison of Cox proportional hazards model, Cox proportional hazards with time-varying coefficients model, and lognormal accelerated failure time model: Application in time to event analysis of melioidosis patients

Author: Kamaruddin MARDHIAH ¹ ; Kamaruddin MARDHIAH ² ; Nadiah WAN-ARFAH ² ; Nyi NAING ³ ; Muhammad HASSAN ⁴ ; Huan-Keat CHAN ⁴
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1. Faculty of Entrepreneurship and Business, Universiti Malaysia Kelantan
2. Faculty of Health Sciences, Universiti Sultan Zainal Abidin
3. Faculty of Medicine, Universiti Sultan Zainal Abidin
4. Clinical Research Center, Hospital Sultanah Bahiyah, Ministry of Health Malaysia
Publication Type:Journal Article
Keywords: Accelerated failure time survival analysis; Cox proportional hazards; Lognormal; Melioidosis; Mortality; Parametric model; Time-dependent; Time-to-event; Timevarying
From: Asian Pacific Journal of Tropical Medicine 2022;15(3):128-134
CountryChina
Language:Chinese
Abstract: Objective: To compare the prognostic factors of mortality among melioidosis patients between lognormal accelerated failure time (AFT), Cox proportional hazards (PH), and Cox PH with timevarying coefficient (TVC) models. Methods: A retrospective study was conducted from 2014 to 2019 among 453 patients who were admitted to Hospital Sultanah Bahiyah, Kedah and Hospital Tuanku Fauziah, Perlis in Northern Malaysia due to confirmed-cultured melioidosis. The prognostic factors of mortality from melioidosis were obtained from AFT survival analysis, and Cox s models and the findings were compared by using the goodness of fit methods. The analyses were done by using Stata SE version 14.0. Results: A total of 242 patients (53.4%) survived. In this study, the median survival time of melioidosis patients was 30.0 days (95% CI 0.0-60.9). Six significant prognostic factors were identified in the Cox PH model and Cox PH-TVC model. In AFT survival analysis, a total of seven significant prognostic factors were identified. The results were found to be only a slight difference between the identified prognostic factors among the models. AFT survival showed better results compared to Cox's models, with the lowest Akaike information criteria and best fitted Cox-snell residuals. Conclusions: AFT survival analysis provides more reliable results and can be used as an alternative statistical analysis for determining the prognostic factors of mortality in melioidosis patients in certain situations.