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Abstract Introduction CAR T cell treatment is the standard of care for patients (pts) with primary refractory and relapsed large B-cell lymphoma (LBCL) within the first 12 months of chemoimmunotherapy, or for those unfit for autologous stem cell transplant (ASCT) regardless of timing of relapse. Consequently, the role of ASCT is limited to pts with late relapse (>12 months) who achieve a complete or partial response (CR or PR) to salvage therapy and are deemed eligible for ASCT based on comorbidities and performance status. In this report, we evaluated post-ASCT outcomes in this population of pts. Methods We conducted a retrospective cohort study using publicly available data from the Center for International Blood and Marrow Transplant Research (CIBMTR). Adult pts (age ≥18 years) with DLBCL, NOS, and high-grade large B-cell lymphomas (HGBL) who relapsed after having responded to initial treatment and who remained on response for at least 12 months since diagnosis were selected. We considered for this analysis only pts who achieved a CR or PR after salvage treatment at the time of relapse, documented on pre-ASCT CT or PET scan (per the 2014 Lugano definition). CIBMTR databases used for this study included pts who received ASCT from 2013 to 2021. We compared baseline characteristics between ASCT in CR vs PR using the Wilcoxon rank sum test for continuous variables and the Pearson's χ2 test for categorical variables after ignoring missing data. Primary endpoints included Progression-free survival (PFS) and overall survival (OS). Non-relapse mortality (NRM) and relapse rate were among the secondary endpoints. Results 182 were included in the analysis: 100 were in CR and 82 in PR before ASCT. The median age at ASCT was 60 years (range, 26-79). Race distribution was similar across CR and PR pts. Advanced-stage disease at diagnosis (stage III–IV) was seen in 61% of CR pts and 55% of PR pts. High-grade B-cell lymphoma (HGBL) with MYC and BCL2 and/or BCL6 rearrangements was similar in the CR and PR groups (7% vs 4%). The median number of lines of treatment before ASCT were identical in CR and PR pts (N=2). BEAM was the most frequently used transplant conditioning regimen in both groups (80%). Median follow-up after ASCT was 34 months (range, 1–95): it was 37 months (range 1-95) in the CR group and 26 months (range 1-79) in the PR group For the entire cohort, OS at 3 years was 67.6% and PFS was 50.6%. NRM was 1.7% at 100 days and 3.4% at 1 year. Cumulative incidence of relapse at 3 years was 43.9%. The NRM analysis showed no statistically significant difference between pts in CR and PR. The 3-year OS for CR pts was 73.9%% compared to 59.4% for PR pts (95% CI, 0.334-0.99; p=.044). The 3-year PFS for CR pts was 59.8%, compared to 38.6% for PR pts (95% CI, 0.321-0.784; p=.001). The median PFS for CR pts was 52.01 months, compared to 14.05 months for PR pts. The cumulative incidence of relapse at 3 years in CR and PR pts was 35.2% vs 55.7%, respectively (95% CI, 0.311-0.811; p=.003.). Higher age (HR 1.03; p=.026) and number of previous lines of treatment (HR 1.43; p=.002) were associated with inferior OS. For PFS, no variables showed any significant impact in univariable analysis. The stepwise multivariable analysis showed that only the number of previous treatments had a significant impact on the OS (p=.009), while undergoing ASCT on a PR was the only factor significantly associated with shorter PFS (HR 1.41; 95% CI, 1.09-1.82; p=.029). Conclusion This dataset supports that ASCT provides high efficacy in pts experiencing late relapses (after 12 months) achieving CR following pre-transplant savage and validates the value of achieving CR. Outcomes for PR are inferior, and this analysis provides a benchmark for future investigations. At this time, until convincing on other non-transplant treatment show superior outcomes in this setting, ASCT remains a standard of care for fit pts with chemo-sensitive late relapsed DLBCL. In this group of patients, who have a better prognosis compared to patients who relapse within a year the major hurdle is achieving a remission pre-ASCT.

Importance Transthyretin amyloid cardiomyopathy (ATTR-CM) is underdiagnosed despite expanding treatment options. Objective To develop and evaluate an artificial intelligence (AI)–augmented clinical program for ATTR-CM detection. Design, Setting, and Participants This nonrandomized clinical trial involved constructing an AI model, ATTRACTnet, using electrocardiogram waveforms, echocardiographic measurements, demographics, and diagnosis codes for orthopedic manifestations of amyloidosis. A single-system, multisite, single-arm, open-label trial was conducted to evaluate its real-world performance. The model was trained and validated at a large academic referral site for ATTR-CM with external validation at an academic site. The trial was conducted as a single-system, multisite trial. Patients with left ventricular (LV) wall thickness 12 mm or more and an ATTRACTnet score 0.5 or higher were eligible. Exclusions included prior ATTR-CM testing, hypertrophic cardiomyopathy, expected life span less than 1 year, nursing home residence, advanced dementia, or LV wall thickness less than 14 mm explained by uncontrolled hypertension or moderate/severe aortic stenosis. Intervention Eligible patients were notified and offered nuclear scintigraphy testing, monoclonal protein testing, and follow-up care on agreement from the treating physician. Main Outcomes and Measure The primary outcome was a diagnosis of ATTR-CM by consensus criteria. ATTR-CM testing positivity was compared with historical and contemporary controls. Results ATTRACTnet was developed in an internal test set of 799 patients (mean [SD] age, 75.1 [11.1] years; 516 [64.7%] male and 283 [35.3%] female) using 5-fold cross-validation with an additional external test set of 422 patients. It had good discrimination for ATTR-CM detection with an area under the receiver operator characteristic curve of 0.85 (5-fold cross-validation, 0.77-0.85) in the internal set and 0.82 (95% CI, .81-0.83) in the external test set with similar performance in Hispanic, non-Hispanic Black, and non-Hispanic White patients. A total of 1471 patients were identified with positive AI model scores 0.5 or more during the study period, with 256 eligible patients who met study criteria. Of these patients, 50 underwent amyloidosis testing after physician and patient approval; 24 (48%) were diagnosed with ATTR-CM, and 21 (88%) initiated treatment within 3 months. The positivity rate was more than 2.8 times higher than historical controls (15.3%; 95% CI, 13.1%-17.9%; P < .001), with an 18% relative increase in new diagnoses vs the prior year. Conclusions and Relevance AI-augmented screening may improve ATTR-CM detection and identify patients who are missed by usual care. Prospective randomized trials are needed to determine if outcomes are improved. Trial Registration ClinicalTrials.gov Identifier: NCT06469372