Error Rates for Unvalidated Medical Age Assessment Procedures

TL;DR

This paper analyzes the accuracy of Swedish medical age assessment procedures using a stochastic model, revealing potential high error rates and discrepancies in biological maturity indicators.

Contribution

It introduces a stochastic model to evaluate the validity of age indicators and uncovers possible systematic errors in the assessment procedure.

Findings

Femur maturity appears earlier than tooth maturity contrary to claims.

Classification error rates for some groups may reach 10-30%, possibly up to 50%.

Observed data shows unexpected combinations of maturity indicators.

Abstract

During 2014-15 Sweden received asylum applications from more than 240.000 people, of which more than 40.000 were termed unaccompanied minors. In a large number of cases, claims by asylum seekers of being below 18 years were not trusted by Swedish authorities. To handle the situation, the Swedish national board of forensic medicine (R\"attsmedicinalverket, RMV) was assigned by the government to create a centralized system for medical age assessments. RMV introduced a procedure including two biological age indicators; x-ray of the third molars and magnetic resonance imaging of the distal femoral epiphysis. In 2017 a total of 9617 males and 337 females were subjected to this procedure. No validation study for the procedure was however published, and the observed number of cases with different maturity combinations in teeth and femur were unexpected given the claims originally made by RMV. Such unexpected results might be caused by systematic errors and need to be analysed thoroughly. In the present paper we present a general stochastic model enabling us to study which combinations of age indicator model parameters and age population profiles are consistent with the observed 2017 data for males. We find that, contrary to some RMV claims, maturity of the femur, as observed by RMV, appears on average well before maturity of teeth. Although results naturally contain much uncertainty, we find that classification error rates for certain groups who based on the RMV procedure are classified as above 18 years may be around 10-30%, possibly as high as 50%.