RESUMO
Inadequate diagnostics compromise cancer care across lower- and middle-income countries (LMICs). We hypothesized that an inexpensive gene expression assay using paraffin-embedded biopsy specimens from LMICs could distinguish lymphoma subtypes without pathologist input. We reviewed all biopsy specimens obtained at the Instituto de Cancerología y Hospital Dr. Bernardo Del Valle in Guatemala City between 2006 and 2018 for suspicion of lymphoma. Diagnoses were established based on the World Health Organization classification and then binned into 9 categories: nonmalignant, aggressive B-cell, diffuse large B-cell, follicular, Hodgkin, mantle cell, marginal zone, natural killer/T-cell, or mature T-cell lymphoma. We established a chemical ligation probe-based assay (CLPA) that quantifies expression of 37 genes by capillary electrophoresis with reagent/consumable cost of approximately $10/sample. To assign bins based on gene expression, 13 models were evaluated as candidate base learners, and class probabilities from each model were then used as predictors in an extreme gradient boosting super learner. Cases with call probabilities < 60% were classified as indeterminate. Four (2%) of 194 biopsy specimens in storage <3 years experienced assay failure. Diagnostic samples were divided into 70% (n = 397) training and 30% (n = 163) validation cohorts. Overall accuracy for the validation cohort was 86% (95% confidence interval [CI]: 80%-91%). After excluding 28 (17%) indeterminate calls, accuracy increased to 94% (95% CI: 89%-97%). Concordance was 97% for a set of high-probability calls (n = 37) assayed by CLPA in both the United States and Guatemala. Accuracy for a cohort of relapsed/refractory biopsy specimens (n = 39) was 79% and 88%, respectively, after excluding indeterminate cases. Machine-learning analysis of gene expression accurately classifies paraffin-embedded lymphoma biopsy specimens and could transform diagnosis in LMICs.
Assuntos
Países em Desenvolvimento , Linfoma de Células T Periférico , Biópsia , HumanosRESUMO
BACKGROUND: Treatment-related mortality and abandonment of therapy are major barriers to successful treatment of childhood acute lymphoblastic leukemia (ALL) in the developing world. PROCEDURE: A collaboration was undertaken between Instituto Nacional de Cancerologia (Bogota, Colombia), which serves a poor patient population in an upper-middle income country, and Dana-Farber/Boston Children's Cancer and Blood Disorders Center (Boston, USA). Several interventions aimed at reducing toxic deaths and abandonment were implemented, including a reduced-intensity treatment regimen and a psychosocial effort targeting abandonment. We performed a cohort study to assess impact. RESULTS: The Study Population comprised 99 children with ALL diagnosed between 2007 and 2010, and the Historic Cohort comprised 181 children treated prior to the study interventions (1995-2004). Significant improvements were achieved in the rate of deaths in complete remission (13% to 3%; P = 0.005), abandonment (32% to 9%; P < 0.001), and event-free survival with abandonment considered an event (47% to 65% at 2 years; P = 0.016). However, relapse rate did not improve. Medically unnecessary treatment delays were common, and landmark analysis revealed that initiating the PIII phase of therapy ≥4 weeks delayed predicted markedly inferior disease-free survival (P = 0.016). Conversely, patients who received therapy without excessive delays had outcomes approaching those achieved in high-income countries. CONCLUSIONS: Implementation of a twinning program was followed by reductions in abandonment and toxic deaths, but relapse rate did not improve. Inappropriate treatment delays were common and strongly predicted treatment failure. These findings highlight the importance of adherence to treatment schedule for effective therapy of ALL.