Low-titer autoantibodies and overdiagnosis: impact on testing cascades.
DOI:
https://doi.org/10.70577/3j0hk355Keywords:
autoanticuerpos, baja titulación, sobrediagnóstico, cascadas diagnósticas, gobernanza diagnóstica, laboratorio clínico, sobreutilización, eficiencia diagnóstica.Abstract
The detection of low-titer autoantibodies in clinical practice represents an increasing challenge due to its association with overdiagnosis and the activation of diagnostic testing cascades that increase resource utilization, unnecessary medicalization, and prolonged care pathways without proportional clinical benefit. The objective of this study was to analyze the impact of low-titer autoantibodies on the generation of diagnostic cascades and to evaluate how modifications in interpretative thresholds and institutional governance of laboratory test demand influence confirmatory efficiency and the reduction of overutilization. The methodology followed a quantitative explanatory approach based on secondary data from governmental reports and national and international organizations, complemented by advanced statistical modeling using segmented time series regression and multilevel mixed-effects models to estimate institutional variability and the effect of structural interventions. The results showed that low titers account for the highest proportion of positive findings but exhibit limited confirmatory yield, whereas raising interpretative thresholds significantly reduces the volume of positives entering diagnostic pathways and improves predictive value. In addition, a substantial proportion of variability in cascade activation was attributable to organizational factors rather than clinical differences, particularly the absence of formal protocols, non-contextualized interpretation of results, and lack of repetition control. Overall, the findings indicate that low-titer positivity functions as a structural trigger of overutilization when not integrated with strict clinical criteria and institutional mechanisms regulating laboratory test demand.
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