Towards better triage of infants suspected of cow's milk allergy: development of a preliminary multivariable diagnostic index
The double-blind placebo-controlled food challenge (DBPCFC) is currently the gold standard to diagnose cow's milk allergy (CMA). However, DBPCFCs are burdensome, expensive and require specialised facilities. For primary care physicians, selective and consistent referral to DBPCFC of infants suspected of CMA may be difficult. The objective of this study was to assess the predictive value of clinical parameters for a positive DBPCFC in infants suspected of CMA. Clinical data from 124 infants suspected of CMA that had undergone a DBPCFC were collected. Out of a total of 23 parameters, nine candidate predictors were selected on clinical grounds. We used bootstrapped logistic regression analysis to find a more parsimonious and practical model. The prevalence of a positive DBPCFC was 34.7 % (95 % CI from 27 to 43). A well-calibrated diagnostic model containing as predictors abdominal cramps, inconsolable crying and the objective SCORAD index discriminated moderately well between infants with and without a positive DBPCFC. The area under the ROC curve was 0.68 (95 % CI from 0.58 to 0.78). The fifth and 95th percentiles of the positive DBPCFC predictive probability distribution were 17 and 73 % (17 and 59 % after correction for over-optimism). We conclude that a diagnostic model with three clinical parameters may be used for better referral of children suspected of CMA and the decision to either initially perform an open food challenge or directly perform a DBPCFC. Large prospective studies are needed to validate these findings and provide additional precision.
KeywordsCow's milk allergy Infants Diagnosis Logistic regression Retrospective cohort study
Bootstrap inclusion fraction
Cow's milk allergy
Cow's milk protein
Double-blind placebo-controlled food challenge
SCORing atopic dermatitis