Methods of competing risks flexible parametric modeling for estimation of the risk of the first disease among HIV infected men

Sahar Nouri,Kazem Mohammad,Noori Akhtar-Danesh,Mahdi Yaseri,Mohammad Ali Mansournia,Mahmood Mahmoudi

doi:10.1186/s12874-020-0900-z

Abstract

BackgroundPatients infected with the Human Immunodeficiency Virus (HIV) are susceptible to many diseases. In these patients, the occurrence of one disease alters the chance of contracting another. Under such circumstances, methods for competing risks are required. Recently, competing risks analyses in the scope of flexible parametric models have risen to address this requirement. These lesser-known analyses have considerable advantages over conventional methods.MethodsUsing data from Multi Centre AIDS Cohort Study (MACS), this paper reviews and applies methods of competing risks flexible parametric models to analyze the risk of the first disease (AIDS or non-AIDS) among HIV-infected patients. We compared two alternative subdistribution hazard flexible parametric models (SDHFPM1 and SDHFPM2) with the Fine & Gray model. To make a complete inference, we performed cause-specific hazard flexible parametric models for each event separately as well.ResultsBoth SDHFPM1 and SDHFPM2 provided consistent results regarding the magnitude of coefficients and risk estimations compared with estimations obtained from the Fine & Gray model, However, competing risks flexible parametric models provided more efficient and smoother estimations for the baseline risks of the first disease. We found that age at HIV diagnosis indirectly affected the risk of AIDS as the first event by increasing the number of patients who experience a non-AIDS disease prior to AIDS among > 40 years. Other significant covariates had direct effects on the risks of AIDS and non-AIDS.DiscussionThe choice of an appropriate model depends on the research goals and computational challenges. The SDHFPM1 models each event separately and requires calculating censoring weights which is time-consuming. In contrast, SDHFPM2 models all events simultaneously and is more appropriate for large datasets, however, when the focus is on one particular event SDHFPM1 is more preferable.

Highlights

Patients infected with the Human Immunodeficiency Virus (HIV) are susceptible to many diseases
Patients who were diagnosed with Acquired Immunodeficiency Syndrome (AIDS) as the first event tended to be younger, have more prevalence in 1984–85 and 1987–90 recruitments, lower CD4, higher CD8, and higher RBC in comparison with patients who were diagnosed with non-AIDS diseases as the first event
The rest of this section is concentrated on the results of SDHFPM1 and Cause-Specific Hazard Flexible Parametric Model (CSHFPM)

Summary

Introduction

Patients infected with the Human Immunodeficiency Virus (HIV) are susceptible to many diseases In these patients, the occurrence of one disease alters the chance of contracting another. The occurrence of one disease alters the chance of contracting another Under such circumstances, methods for competing risks are required. One solution to assess an unbiased estimate of the risk of the event of interest is restricting the analysis to competing events where the follow up for a patient ends at the onset of the first event, and not focusing on multiple events in a patient [9,10,11] In this scenario, traditional survival analysis presumes that only one event can occur is not valid and this calls for special methods for competing risks, [5, 12]. It is defined as the probability of failure from the event of interest in an interval of time from the beginning of the study until a particular time when it is quite clear how many subjects experienced competing events

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