Author(s): Parimon T, Au DH, Martin PJ, Chien JW
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Abstract BACKGROUND: Despite recent advances, mortality rates after allogeneic hematopoietic cell transplantation remain high and cannot be accurately predicted. OBJECTIVE: To develop a reliable and valid predictor of all-cause mortality during the first 2 years after allogeneic hematopoietic cell transplantation. DESIGN: Retrospective cohort. SETTING: Tertiary hematopoietic cell transplantation center. PATIENTS: Patients (n = 2802) who received a first hematopoietic cell transplant between 1990 and 2002 were assigned to a development group or a validation group. MEASUREMENTS: Potential predictor variables were assessed with univariate and multivariable Cox proportional hazards methods to generate a prediction model. The c-statistic was calculated for 5 validation cohorts to assess model performance across early and late time periods and among patients with different diagnoses. RESULTS: The authors constructed a 50-point Pretransplantation Assessment of Mortality (PAM) score that incorporated 8 pretransplantation clinical variables: patient age, donor type, disease risk, conditioning regimen, FEV1, carbon monoxide diffusion capacity, serum creatinine level, and serum alanine aminotransferase concentration. The risk for death within 2 years for patients with PAM scores in the highest category was significantly higher than for those with scores in the lowest category. C-statistic values ranged from 0.69 to 0.76 for all validation cohorts. LIMITATIONS: The predictor model was not validated in an external cohort and is only useful for predicting the risk for death within the first 2 years after hematopoietic cell transplantation. CONCLUSIONS: Integrating pretransplantation clinical variables into a single score reliably predicts survival within 2 years after allogeneic hematopoietic cell transplantation. Accurate estimates of the risk for death may be useful in clinical trials and in epidemiologic studies. Such information can also be used to help physicians counsel patients regarding the expected outcomes of this potentially curative procedure.
This article was published in Ann Intern Med
and referenced in Journal of Data Mining in Genomics & Proteomics