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;Nadiah Wan-Arfah;Nyi Nyi Naing;Muhammad Radzi Abu Hassan;Huan-Keat Chan;Faculty of Entrepreneurship and Business, Universiti Malaysia Kelantan;Faculty of Health Sciences, Universiti Sultan Zainal Abidin;Faculty of Medicine, Universiti Sultan Zainal Abidin;Clinical Research Center, Hospital Sultanah Bahiyah, Ministry of Health Malaysia;

【Institution】

Faculty of Entrepreneurship and Business, Universiti Malaysia Kelantan;Faculty of Health Sciences, Universiti Sultan Zainal Abidin;Faculty of Medicine, Universiti Sultan Zainal Abidin;Clinical Research Center, Hospital Sultanah Bahiyah, Ministry of Health Malaysia;

【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.

【Keywords】

Cox proportional hazards;;Time-dependent;;Timevarying;;Accelerated failure time survival analysis;;Lognormal;;Parametric model;;Time-to-event;;Melioidosis;;Mortality

References

To explore the background and basis of the node document

Springer Journals Database

Total: 17 articles

  • [1] Kamaruddin Mardhiah;Nadiah Wan-Arfah;Nyi Nyi Naing;Muhammad Radzi Abu Hassan;Huan-Keat Chan;Faculty of Entrepreneurship and Business, Universiti Malaysia Kelantan;Faculty of Health Sciences, Universiti Sultan Zainal Abidin, Gong Badak Campus;Faculty of Medicine, Universiti Sultan Zainal Abidin;Clinical Research Center, Hospital Sultanah Bahiyah, Ministry of Health Malaysia;, Predictors of in-hospital mortality by logistic regression analysis among melioidosis patients in Northern Malaysia: A retrospective study, Asian Pacific Journal of Tropical Medicine,
  • [2] Sayehmiri Kourosh;;Eshraghian Mohammad ;;Mohammad Kazem;;Alimoghaddam Kamran;;Foroushani Abbas;;Zeraati Hojjat;;Golestan Banafsheh;;Ghavamzadeh Ardeshir, Prognostic factors of survival time after hematopoietic stem cell transplant in acute lymphoblastic leukemia patients: Cox proportional hazard versus accelerated failure time models, Journal of Experimental & Clinical Cancer Research,
  • [3] Hassan Muhammad ;;Pani Subhada ;;Peng Ng ;;Voralu Kirtanaa;;Vijayalakshmi Natesan;;Mehanderkar Ranjith;;Aziz Norasmidar ;;Michael Edwin, Incidence, risk factors and clinical epidemiology of melioidosis: a complex socio-ecological emerging infectious disease in the Alor Setar region of Kedah, Malaysia, BMC Infectious Diseases,
  • [4] Altman D G;;De Stavola B L;;Love S B;;Stepniewska K A, Review of survival analyses published in cancer journals., British journal of cancer,

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