Development of the Lung Transplant Frailty Scale (LT-FS).

BACKGROUND: Existing measures of frailty developed in community dwelling older adults may misclassify frailty in lung transplant candidates. We aimed to develop a novel frailty scale for lung transplantation with improved performance characteristics. METHODS: We measured the short physical performance battery (SPPB), fried frailty phenotype (FFP), Body Composition, and serum Biomarkers representative of putative frailty mechanisms. We applied a 4-step established approach (identify frailty domain variable bivariate associations with the outcome of waitlist delisting or death; build models sequentially incorporating variables from each frailty domain cluster; retain variables that improved model performance ability by c-statistic or AIC) to develop 3 candidate "Lung Transplant Frailty Scale (LT-FS)" measures: 1 incorporating readily available clinical data; 1 adding muscle mass, and 1 adding muscle mass and research-grade Biomarkers. We compared construct and predictive validity of LT-FS models to the SPPB and FFP by ANOVA, ANCOVA, and Cox proportional-hazard modeling. RESULTS: In 342 lung transplant candidates, LT-FS models exhibited superior construct and predictive validity compared to the SPPB and FFP. The addition of muscle mass and Biomarkers improved model performance. Frailty by all measures was associated with waitlist disability, poorer HRQL, and waitlist delisting/death. LT-FS models exhibited stronger associations with waitlist delisting/death than SPPB or FFP (C-statistic range: 0.73-0.78 vs. 0.57 and 0.55 for SPPB and FFP, respectively). Compared to SPPB and FFP, LT-FS models were generally more strongly associated with delisting/death and improved delisting/death net reclassification, with greater improvements with increasing LT-FS model complexity (range: 0.11-0.34). For example, LT-FS-Body Composition hazard ratio for delisting/death: 6.0 (95%CI: 2.5, 14.2), SPPB HR: 2.5 (95%CI: 1.1, 5.8), FFP HR: 4.3 (95%CI: 1.8, 10.1). Pre-transplant LT-FS frailty, but not SPPB or FFP, was associated with mortality after transplant. CONCLUSIONS: The LT-FS is a disease-specific physical frailty measure with face and construct validity that has superior predictive validity over established measures.

Subphenotypes of frailty in lung transplant candidates.

Heterogeneous frailty pathobiology might explain the inconsistent associations observed between frailty and lung transplant outcomes. A Subphenotype analysis could refine frailty measurement. In a 3-center pilot cohort study, we measured frailty by the Short Physical Performance Battery, body composition, and serum biomarkers reflecting causes of frailty. We applied latent class modeling for these baseline data. Next, we tested class construct validity with disability, waitlist delisting/death, and early postoperative complications. Among 422 lung transplant candidates, 2 class model fit the best (P = .01). Compared with Subphenotype 1 (n = 333), Subphenotype 2 (n = 89) was characterized by systemic and innate inflammation (higher IL-6, CRP, PTX3, TNF-R1, and IL-1RA); mitochondrial stress (higher GDF-15 and FGF-21); sarcopenia; malnutrition; and lower hemoglobin and walk distance. Subphenotype 2 had a worse disability and higher risk of waitlist delisting or death (hazards ratio: 4.0; 95% confidence interval: 1.8-9.1). Of the total cohort, 257 underwent transplant (Subphenotype 1: 196; Subphenotype 2: 61). Subphenotype 2 had a higher need for take back to the operating room (48% vs 28%; P = .005) and longer posttransplant hospital length of stay (21 days [interquartile range: 14-33] vs 18 days [14-28]; P = .04). Subphenotype 2 trended toward fewer ventilator-free days, needing more postoperative extracorporeal membrane oxygenation and dialysis, and higher need for discharge to rehabilitation facilities (P ≤ .20). In this early phase study, we identified biological frailty Subphenotypes in lung transplant candidates. A hyperinflammatory, sarcopenic Subphenotype seems to be associated with worse clinical outcomes.

Electrostatic Complementarity of T-Cell Receptor-Alpha CDR3 Domains and Mutant Amino Acids Is Associated with Better Survival Rates for Sarcomas.

While sarcoma immunology has advanced with regard to basic, and even some applied topics, this disease has not been subject to more recent immunogenomics approaches. Thus, we assessed the immune receptor recombinations available from the cancer genome atlas (TCGA) sarcoma database via tumor sample exome and RNASeq files. Results indicated that recovery of T-cell receptor-alpha recombination reads (TRA) correlated with a better survival rate, with the expression of T-cell biomarkers, and with tumor sample apoptosis signatures consistent with the longer patient survival times. Furthermore, samples representing TRA complementarity determining region-3 (CDR3) net charge per residue (NCPR) based complementarity with the corresponding sarcoma mutanome had a better survival rate, and more granzyme expression, than samples lacking such complementarity. By specifically using RNASeq-recovered TRA CDR3s and related NCPR assessments, three genes, TP53, ATRX, and RB1, were identified as being key components of the mutanome-based complementarity. Thus, these genes may represent key immune system targets for soft tissue sarcomas. Also, several key results from above were reproduced with a pediatric osteosarcoma dataset, work that led to identification of MUC6 mutations as potentially linked to a strong immune response. In sum, TRA CDR3s are likely to be important prognostic indicators, and possibly a beginning tool for immunotherapy development strategies, for adult and pediatric sarcomas.