Comparison of methods to correct survival estimates and survival regression analysis on a large HIV African cohort.

Julie Henriques, Mar Pujades-Rodriguez, Megan McGuire, Elisabeth Szumilin, Jean Iwaz, Jean-François Etard, René Ecochard

PloS one 2012

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The evaluation of HIV treatment programs is generally based on an estimation of survival among patients receiving antiretroviral treatment (ART). In large HIV programs, loss to follow-up (LFU) rates remain high despite active patient tracing, which is likely to bias survival estimates and survival regression analyses. We compared uncorrected survival estimates derived from routine program data with estimates obtained by applying six correction methods that use updated outcome data by a field survey targeting LFU patients in a rural HIV program in Malawi. These methods were based on double-sampling and differed according to the weights given to survival estimates in LFU and non-LFU subpopulations. We then proposed a correction of the survival regression analysis. Among 6,727 HIV-infected adults receiving ART, 9% were LFU after one year. The uncorrected survival estimates from routine data were 91% in women and 84% in men. According to increasing sophistication of the correction methods, the corrected survival estimates ranged from 89% to 85% in women and 82% to 77% in men. The estimates derived from uncorrected regression analyses were highly biased for initial tuberculosis mortality ratios (RR; 95% CI: 1.07; 0.76-1.50 vs. 2.06 to 2.28 with different correction weights), Kaposi sarcoma diagnosis (2.11; 1.61-2.76 vs. 2.64 to 3.9), and year of ART initiation (1.40; 1.17-1.66 vs. 1.29 to 1.34). In HIV programs with high LFU rates, the use of correction methods based on non-exhaustive double-sampling data are necessary to minimise the bias in survival estimates and survival regressions.

Citation

Julie Henriques, Mar Pujades-Rodriguez, Megan McGuire, Elisabeth Szumilin, Jean Iwaz, Jean-François Etard, René Ecochard. Comparison of methods to correct survival estimates and survival regression analysis on a large HIV African cohort. PloS one. 2012;7(2):e31706