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A novel Iowa-Mayo validated composite risk assessment tool for allogeneic stem cell transplantation survival outcome prediction.

ABSTRACT: Allogeneic hematopoietic stem cell transplantation (HSCT) is a curative option for many hematologic conditions and is associated with considerable morbidity and mortality. Therefore, prognostic tools are essential to navigate the complex patient, disease, donor, and transplant characteristics that differentially influence outcomes. We developed a novel, comprehensive composite prognostic tool. Using a lasso-penalized Cox regression model (n = 273), performance status, HCT-CI, refined disease-risk index (rDRI), donor and recipient CMV status, and donor age were identified as predictors of disease-free survival (DFS). The results for overall survival (OS) were similar except for recipient CMV status not being included in the model. Models were validated in an external dataset (n = 378) and resulted in a c-statistic of 0.61 and 0.62 for DFS and OS, respectively. Importantly, this tool incorporates donor age as a variable, which has an important role in HSCT outcomes. This needs to be further studied in prospective models. An easy-to-use and a web-based nomogram can be accessed here: https://allohsctsurvivalcalc.iowa.uiowa.edu/ .

SUBMITTER: Nadiminti K

PROVIDER: S-EPMC8606004 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

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A novel Iowa-Mayo validated composite risk assessment tool for allogeneic stem cell transplantation survival outcome prediction.

Nadiminti Kalyan K Langer Kimberly K Shabbir Ehsan E Hefazi Mehrdad M Dozeman Lindsay L Jethava Yogesh Y Loeffler Bradley B AlKhateeb Hassan B HB Litzow Mark M Patnaik Mrinal M Shah Mithun M Hogan William W Farooq Umar U Silverman Margarida M Mott Sarah L SL

Blood cancer journal 20211120 11

Allogeneic hematopoietic stem cell transplantation (HSCT) is a curative option for many hematologic conditions and is associated with considerable morbidity and mortality. Therefore, prognostic tools are essential to navigate the complex patient, disease, donor, and transplant characteristics that differentially influence outcomes. We developed a novel, comprehensive composite prognostic tool. Using a lasso-penalized Cox regression model (n = 273), performance status, HCT-CI, refined disease-ris ...[more]

PMID: 34802042

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Project description:Optimizing natural killer (NK) cell alloreactivity could further improve outcome after allogeneic hematopoietic cell transplantation (alloHCT). The donor's Killer-cell Immunoglobulin-like Receptor (KIR) genotype may provide important information in this regard. In the past decade, different models have been proposed aiming at maximizing NK cell activation by activating KIR-ligand interactions or minimizing inhibitory KIR-ligand interactions. Alternative classifications intended predicting outcome after alloHCT by donor KIR-haplotypes. In the present study, we aimed at validating proposed models and exploring more classification approaches. To this end, we analyzed samples stored at the Collaborative Biobank from HLA-compatible unrelated stem cell donors who had donated for patients with acute myeloid leukemia (AML) or myelodysplastic neoplasm (MDS) and whose outcome data had been reported to EBMT or CIBMTR. The donor KIR genotype was determined by high resolution amplicon-based next generation sequencing. We analyzed data from 5,017 transplants. The median patient age at alloHCT was 56 years. Patients were transplanted for AML between 2013 and 2018. Donor-recipient pairs were matched for HLA-A, -B, -C, -DRB1, and -DQB1 (79%) or had single HLA mismatches. Myeloablative conditioning was given to 56% of patients. Fifty-two percent of patients received anti-thymocyte-globulin-based graft-versus-host disease prophylaxis, 32% calcineurin-inhibitor-based prophylaxis, and 7% post-transplant cyclophosphamide-based prophylaxis. We tested several previously reported classifications in multivariable regression analyses but could not confirm outcome associations. Exploratory analyses in 1,939 patients (39%) who were transplanted from donors with homozygous centromeric (cen) or telomeric (tel) A or B motifs, showed that the donor cen B/B-tel A/A diplotype was associated with a trend to better event-free survival (HR 0.84, p=.08) and reduced risk of non-relapse mortality (NRM) (HR 0.65, p=.01). When we further dissected the contribution of B subtypes, we found that only the cen B01/B01-telA/A diplotype was associated with a reduced risk of relapse (HR 0.40, p=.04) while all subtype combinations contributed to a reduced risk of NRM. This exploratory finding has to be validated in an independent data set. In summary, the existing body of evidence is not (yet) consistent enough to recommend use of donor KIR genotype information for donor selection in routine clinical practice.

Project description:Background & aimsPatients with hepatocellular carcinoma (HCC) are selected for liver transplantation (LT) based on pre-LT imaging ± alpha-foetoprotein (AFP) level, but discrepancies between pre-LT tumour assessment and explant are frequent. Our aim was to design an explant-based recurrence risk reassessment score to refine prediction of recurrence after LT and provide a framework to guide post-LT management.MethodsAdult patients who underwent transplantation between 2000 and 2018 for HCC in 47 centres were included. A prediction model for recurrence was developed using competing-risk regression analysis in a European training cohort (TC; n = 1,359) and tested in a Latin American validation cohort (VC; n=1,085).ResultsIn the TC, 76.4% of patients with HCC met the Milan criteria, and 89.9% had an AFP score of ≤2 points. The recurrence risk reassessment (R3)-AFP model was designed based on variables independently associated with recurrence in the TC (with associated weights): ≥4 nodules (sub-distribution of hazard ratio [SHR] = 1.88, 1 point), size of largest nodule (3-6 cm: SHR = 1.83, 1 point; >6 cm: SHR = 5.82, 5 points), presence of microvascular invasion (MVI; SHR = 2.69, 2 points), nuclear grade >II (SHR = 1.20, 1 point), and last pre-LT AFP value (101-1,000 ng/ml: SHR = 1.57, 1 point; >1,000 ng/ml: SHR = 2.83, 2 points). Wolber's c-index was 0.76 (95% CI 0.72-0.80), significantly superior to an R3 model without AFP (0.75; 95% CI 0.72-0.79; p = 0.01). Four 5-year recurrence risk categories were identified: very low (score = 0; 5.5%), low (1-2 points; 15.1%), high (3-6 points; 39.1%), and very high (>6 points; 73.9%). The R3-AFP score performed well in the VC (Wolber's c-index of 0.78; 95% CI 0.73-0.83).ConclusionsThe R3 score including the last pre-LT AFP value (R3-AFP score) provides a user-friendly, standardised framework to design post-LT surveillance strategies, protocols, or adjuvant therapy trials for HCC not limited to the Milan criteria.Clinical trials registrationNCT03775863.Lay summaryConsidering discrepancies between pre-LT tumour assessment and explant are frequent, reassessing the risk of recurrence after LT is critical to further refine the management of patients with HCC. In a large and international cohort of patients who underwent transplantation for HCC, we designed and validated the R3-AFP model based on variables independently associated with recurrence post-LT (number of nodules, size of largest nodule, presence of MVI, nuclear grade, and last pre-LT AFP value). The R3-AFP model including last available pre-LT AFP value outperformed the original R3 model only based on explant features. The final R3-AFP scoring system provides a robust framework to design post-LT surveillance strategies, protocols, or adjuvant therapy trials, irrespective of criteria used to select patients with HCC for LT.

Dataset Information

A novel Iowa-Mayo validated composite risk assessment tool for allogeneic stem cell transplantation survival outcome prediction.

Publications

A novel Iowa-Mayo validated composite risk assessment tool for allogeneic stem cell transplantation survival outcome prediction.

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