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Validation of a transfusion prediction model in head and neck cancer surgery
Nadia L Krupp1, Gregory Weinstein, Ara Chalian
1Department of Otorhinolaryngology-Head and Neck Surgery, University of Pennsylvania, Philadelphia, PA, USA.
Background:
Allogeneic transfusions are necessary in 14% to 80% of patients undergoing major head and neck cancer surgery. Defining the risk for receiving allogeneic transfusion allows for informed decisions regarding appropriateness of type and crossmatch, preoperative autologous blood donation, and priming with erythropoietin. Based on logistic regression analysis of transfusion risk factors in 438 patients, we developed a transfusion prediction risk assessment (TPRA) model to determine the need for transfusion based on the preoperative hemoglobin value, tumor stage, and need for flap reconstruction.
Objective:
To examine the utility of this TPRA model in clinical practice by assessing the performance of the model in a validation set of patients.
Methods:
Between 1996 and 1999, 125 consecutive patients entered into a clinical care pathway underwent major surgical procedures. The ability of the model to discriminate between patients requiring and those not requiring transfusion was assessed using the area under the receiver operating characteristic curve. The agreement between actual and predicted risks was tested using the chi2 goodness-of-fit statistic.
Results:
The overall transfusion rate was 25%. A 1-U transfusion was required in 7 patients, and multiple units were necessary for 24 patients. Flap reconstruction was required in 63 patients, 44 patients had preoperative anemia by normative values, and 64 had T3/T4 tumors. Among the low-risk non-T3/T4 patients whose preoperative hemoglobin level was normal, the actual/predicted transfusion rate without flap reconstruction was 10%/2%. For high-risk patients with T3/T4 tumors, anemia, and flap reconstruction, the actual/predicted transfusion rate was 43%/65%. The area under the receiver operating characteristic curve was 0.72. The goodness-of-fit statistic indicated lack of fit of the original model, but a recalibrated model fit the observed data well.
Conclusions:
In general, the TPRA model identifies patients at low or high risk for allogeneic transfusion and provides guidelines for preoperative counseling regarding the risk of receiving a transfusion. Knowledge of a patient's risk can help direct cost-effective utilization of type and crossmatch, preoperative autologous blood donation, and preoperative priming with erythropoietin.