MODELLING SURVIVAL DATA OF THALASSAEMIA PATIENTS IN PAKISTAN
AbstractBackground: Fatimid Foundation with its centers serves as a charitable organization for millionsof blood disease carriers in Pakistan. This retrospective survival study is an analysis of theThalassaemia patients registered in Multan centre who are followed up to nine years to assess thegender risk of death. Methods: Data on 120 patients of Thalassaemia during 1994-2002 wasanalyzed. The standard Kaplan-Meier and Nelson-Aalen procedures were used to compare thesurvival function of the male and female patients of Thalassaemia. The statistical significance wasalso assessed using log rank test. The Cox Proportional Hazards (PH) model using a forwardselection procedure was used to identify the potential factors associated with the increase risk ofdeath. Results: By ignoring the censoring, the average survival time of males and females werecalculated to be 1308.1 and 1574.7 days respectively. The average hazard rate for the femalegroup was 0.00033 and for the male group it was 0.00061. The median survival time wasestimated from the Kaplan-Meier survival curves (Males: 1400 days, Females: 1785 days). Underthe censoring mechanism, the mean survival time for males was calculated to be 1465.82 dayswith standard error of 146 days, where as for females it was calculated to be 1855.26 withstandard error of 151.82 days. When considering death as event of interest Under the Coxmodelling approach, we found a male patient of Thalassaemia was 1.484 times more likely to diewhen compared to his female counterpart. When considering the iron over load as the event ofinterest, we found a male patient of Thalassaemia was 1.753 fold more likely to reach excessiveHaemochromatosis level compared to female patient. Conclusion: The analysis reinforces thatfemale group prognosis is better than the male group. Further, our analysis of real survival data setshows that the high status of Haemochromatosis level is associated with the increased risk of deathin patients with Thalassaemia with other possible confounders.Keywords: Censoring; Cox PH model, Kaplan-Meier estimator, Nelson-Aalen estimator, Thalassaemia
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