Abstract Background Breast implant-associated anaplastic large cell lymphoma (BIA-ALCL) is a rare lymphoma associated with textured implants. Earlier detection and timely implant/capsulectomy reduce morbidity and improve outcomes. CD30 is a sensitive biomarker for BIA-ALCL; carbonic anhydrase IX (CA9) has been identified as a complementary marker in effusion samples. Objectives To develop and evaluate a multiplex lateral flow assay (LFA) for CD30 and CA9 in peri-implant seroma fluid/effusions to support rapid clinical triage of suspected BIA-ALCL. Methods Recombinant CD30 and CA9 were spiked into benign seroma matrix to establish assay detection range under defined conditions. A retrospective cohort of 50 seroma samples (25 pathologically confirmed BIA-ALCL; 25 benign seromas) was tested. Performance was assessed by (i) visual interpretation and (ii) image-based quantification (test line/control line ratio, TL/CL) (iii) combined interpretation approach. Sensitivity, specificity, predictive values (study-conditional), and ROC/AUC were calculated. Results In matrix spike-in experiments, CD30 was detectable down to 500 pg/mL; CA9 was detectable down to 1000 pg/mL. In clinical samples, both CD30 and CA9 TL/CL were significantly higher in BIA-ALCL than benign seromas. Visual interpretation yielded 76% sensitivity and 88% specificity. Image-based interpretation increased sensitivity to 96% but reduced specificity to 80%. A prespecified combined interpretation approach maintained 96% sensitivity and 88% specificity (PPV 89%, NPV 96% within this case-control cohort). ROC analysis demonstrated AUC 0.96 for CD30 and 0.85 for CA9. Conclusions In this retrospective cohort, a multiplex CD30/CA9 LFA distinguished BIA-ALCL from benign peri-implant seromas with high sensitivity and favorable study-conditional NPV, supporting feasibility as a rapid triage adjunct to prioritize confirmatory pathology. Prospective studies with standardized pre-analytics, blinded interpretation, and prevalence-representative cohorts are required to establish real-world predictive values and clinical utility.
Xu et al. (Sun,) studied this question.