Real-world applicability of the International Metabolic Prognostic Index in DLBCL: a validation cohort study
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SUBMITTER: Ikeda D
PROVIDER: S-EPMC11021887 | biostudies-literature | 2024 Feb
REPOSITORIES: biostudies-literature
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Project description:PurposeMyelodysplastic syndromes (MDS) are heterogeneous myeloid neoplasms in which a risk-adapted treatment strategy is needed. Recently, a new clinical-molecular prognostic model, the Molecular International Prognostic Scoring System (IPSS-M) was proposed to improve the prediction of clinical outcome of the currently available tool (Revised International Prognostic Scoring System [IPSS-R]). We aimed to provide an extensive validation of IPSS-M.MethodsA total of 2,876 patients with primary MDS from the GenoMed4All consortium were retrospectively analyzed.ResultsIPSS-M improved prognostic discrimination across all clinical end points with respect to IPSS-R (concordance was 0.81 v 0.74 for overall survival and 0.89 v 0.76 for leukemia-free survival, respectively). This was true even in those patients without detectable gene mutations. Compared with the IPSS-R based stratification, the IPSS-M risk group changed in 46% of patients (23.6% and 22.4% of subjects were upstaged and downstaged, respectively).In patients treated with hematopoietic stem cell transplantation (HSCT), IPSS-M significantly improved the prediction of the risk of disease relapse and the probability of post-transplantation survival versus IPSS-R (concordance was 0.76 v 0.60 for overall survival and 0.89 v 0.70 for probability of relapse, respectively). In high-risk patients treated with hypomethylating agents (HMA), IPSS-M failed to stratify individual probability of response; response duration and probability of survival were inversely related to IPSS-M risk.Finally, we tested the accuracy in predicting IPSS-M when molecular information was missed and we defined a minimum set of 15 relevant genes associated with high performance of the score.ConclusionIPSS-M improves MDS prognostication and might result in a more effective selection of candidates to HSCT. Additional factors other than gene mutations can be involved in determining HMA sensitivity. The definition of a minimum set of relevant genes may facilitate the clinical implementation of the score.
| S-EPMC10414702 | biostudies-literature
Project description:Central nervous system (CNS) relapse carries a poor prognosis in diffuse large B-cell lymphoma (DLBCL). Integrating biomarkers into the CNS-International Prognostic Index (CNS-IPI) risk model may improve identification of patients at high risk for developing secondary CNS disease. CNS relapse was analyzed in 1418 DLBCL patients treated with obinutuzumab or rituximab plus cyclophosphamide, doxorubicin, vincristine, prednisone chemotherapy in the phase 3 GOYA study. Cell of origin (COO) was assessed using gene-expression profiling. BCL2 and MYC protein expression was analyzed by immunohistochemistry. The impact of CNS-IPI, COO, and BCL2/MYC dual-expression status on CNS relapse was assessed using a multivariate Cox regression model (data available in n = 1418, n = 933, and n = 688, respectively). High CNS-IPI score (hazard ratio [HR], 4.0; 95% confidence interval [CI], 1.3-12.3; P = .02) and activated B-cell‒like (ABC) (HR, 5.2; 95% CI, 2.1-12.9; P = .0004) or unclassified COO subtypes (HR, 4.2; 95% CI, 1.5-11.7; P = .006) were independently associated with CNS relapse. BCL2/MYC dual-expression status did not impact CNS relapse risk. Three risk subgroups were identified based on the presence of high CNS-IPI score and/or ABC/unclassified COO (CNS-IPI-C model): low risk (no risk factors, n = 450 [48.2%]), intermediate risk (1 factor, n = 408 [43.7%]), and high risk (both factors, n = 75 [8.0%]). Two-year CNS relapse rates were 0.5%, 4.4%, and 15.2% in the respective risk subgroups. Combining high CNS-IPI and ABC/unclassified COO improved CNS relapse prediction and identified a patient subgroup at high risk for developing CNS relapse. The study was registered at www.clinicaltrials.gov as #NCT01287741.
| S-EPMC6396175 | biostudies-literature
Project description:Using data from Ontario Canada, we previously developed machine learning-based algorithms incorporating newborn screening metabolites to estimate gestational age (GA). The objective of this study was to evaluate the use of these algorithms in a population of infants born in Siaya county, Kenya. Cord and heel prick samples were collected from newborns in Kenya and metabolic analysis was carried out by Newborn Screening Ontario in Ottawa, Canada. Postnatal GA estimation models were developed with data from Ontario with multivariable linear regression using ELASTIC NET regularization. Model performance was evaluated by applying the models to the data collected from Kenya and comparing model-derived estimates of GA to reference estimates from early pregnancy ultrasound. Heel prick samples were collected from 1,039 newborns from Kenya. Of these, 8.9% were born preterm and 8.5% were small for GA. Cord blood samples were also collected from 1,012 newborns. In data from heel prick samples, our best-performing model estimated GA within 9.5 days overall of reference GA [mean absolute error (MAE) 1.35 (95% CI 1.27, 1.43)]. In preterm infants and those small for GA, MAE was 2.62 (2.28, 2.99) and 1.81 (1.57, 2.07) weeks, respectively. In data from cord blood, model accuracy slightly decreased overall (MAE 1.44 (95% CI 1.36, 1.53)). Accuracy was not impacted by maternal HIV status and improved when the dating ultrasound occurred between 9 and 13 weeks of gestation, in both heel prick and cord blood data (overall MAE 1.04 (95% CI 0.87, 1.22) and 1.08 (95% CI 0.90, 1.27), respectively). The accuracy of metabolic model based GA estimates in the Kenya cohort was lower compared to our previously published validation studies, however inconsistency in the timing of reference dating ultrasounds appears to have been a contributing factor to diminished model performance.
| S-EPMC10021775 | biostudies-literature
Project description:BackgroundThe original weight loss grading system (WLGS) was developed in western population, which did not perform effectively in cancer patients from China. This study aimed to develop and validate the modified WLGS (mWLGS) in the prognostic assessment of cancer patients in China.MethodsA prospective multicentre real-world cohort study involving 16 842 patients diagnosed with cancer was conducted. Cox regression was used to calculate the hazard ratios for overall survival. Logistic linear regression was used to assess the odds ratio for 90-day outcomes.ResultsWe calculated survival risks for the 25 mWLGS groups and clustered the approximate survival risks. Finally, we revised the prognostic grading system for mWLGS to include five grades of 0-4. Compared with the original WLGS, the mWLGS had a better prognostic differentiation effect in predicting the prognosis of patients with cancer. The survival rate gradually deteriorated with increasing grade of mWLGS, with the survival rate of grade 0 decreasing from 76.4% to 48.2% for grade 4 (76.4 vs. 72.8 vs. 66.1 vs. 57.0 vs. 48.2%, respectively). The mWLGS provides effective prognostic stratification for most site-specific cancers, especially lung and gastrointestinal cancers. High-grade mWLGS is independently associated with an increased risk of poor quality of life and adverse 90-day outcomes. Multivariate Cox regression analysis showed that the mWLGS was an independent prognostic factor for cancer patients in the validation cohorts.ConclusionsCompared with the original WLGS, the mWLGS can better stratify the prognosis of cancer patients. mWLGS is a useful tool for predicting survival, 90-day outcomes, and quality of life in patients with cancer. These analyses may provide new insights into the application of WLGS in cancer patients in China.
| S-EPMC10570064 | biostudies-literature
Project description:PurposeBurkitt lymphoma (BL) has unique biology and clinical course but lacks a standardized prognostic model. We developed and validated a novel prognostic index specific for BL to aid risk stratification, interpretation of clinical trials, and targeted development of novel treatment approaches.MethodsWe derived the BL International Prognostic Index (BL-IPI) from a real-world data set of adult patients with BL treated with immunochemotherapy in the United States between 2009 and 2018, identifying candidate variables that showed the strongest prognostic association with progression-free survival (PFS). The index was validated in an external data set of patients treated in Europe, Canada, and Australia between 2004 and 2019.ResultsIn the derivation cohort of 633 patients with BL, age ≥ 40 years, performance status ≥ 2, serum lactate dehydrogenase > 3× upper limit of normal, and CNS involvement were selected as equally weighted factors with an independent prognostic value. The resulting BL-IPI identified groups with low (zero risk factors, 18% of patients), intermediate (one factor, 36% of patients), and high risk (≥ 2 factors, 46% of patients) with 3-year PFS estimates of 92%, 72%, and 53%, respectively, and 3-year overall survival estimates of 96%, 76%, and 59%, respectively. The index discriminated outcomes regardless of HIV status, stage, or first-line chemotherapy regimen. Patient characteristics, relative size of the BL-IPI groupings, and outcome discrimination were consistent in the validation cohort of 457 patients, with 3-year PFS estimates of 96%, 82%, and 63% for low-, intermediate-, and high-risk BL-IPI, respectively.ConclusionThe BL-IPI provides robust discrimination of survival in adult BL, suitable for use as prognostication and stratification in trials. The high-risk group has suboptimal outcomes with standard therapy and should be considered for innovative treatment approaches.
| S-EPMC9851706 | biostudies-literature
Project description: Not available
| S-EPMC11675332 | biostudies-literature
Project description:The Multidimensional Prognostic Index (MPI), an objective and quantifiable tool based on the Comprehensive Geriatric Assessment, has been shown to predict adverse outcomes in European cohorts. We conducted a validation study of the original MPI, and of adapted versions that accounted for the use of specific drugs and cultural diversity in the assessment of cognition, in older Australians. The capacity of the MPI to predict 12-month mortality was assessed in 697 patients (median age: 80 years; interquartile range: 72-86) admitted to a metropolitan teaching hospital between September 2015 and February 2017. In simple logistic regression analysis, the MPI was associated with 12-month mortality (Low risk: OR reference group; moderate risk: OR 2.50, 95% CI: 1.67-3.75; high risk: OR 4.24, 95% CI: 2.28-7.88). The area under the receiver operating characteristic curve (AUC) for the unadjusted MPI was 0.61 (0.57-0.65) and 0.64 (95% CI: 0.59-0.68) with age and sex adjusted. The adapted versions of the MPI did not significantly change the AUC of the original MPI. The original and adapted MPI were strongly associated with 12-month mortality in an Australian cohort. However, the discriminatory performance was lower than that reported in European studies.
| S-EPMC6912422 | biostudies-literature
Project description: Not available
| S-EPMC10344481 | biostudies-literature
Project description:The increasing knowledge of molecular genetics of acute myeloid leukemia (AML) necessitated the update of previous diagnostic and prognostic schemes, which resulted in the development of the World Health Organization (WHO), the International Consensus Classification (ICC), and the new European LeukemiaNet (ELN) recommendations in 2022. We aimed to provide a real-world application of the new models, unravel differences and similarities, and test their implementation in clinical AML diagnosis. A total of 1001 patients diagnosed with AML were reclassified based on the new schemes. The overall diagnostic changes between the WHO 2016 and the WHO 2022 and ICC classifications were 22.8% and 23.7%, respectively, with a 13.1% difference in patients' distribution between ICC and WHO 2022. The 2022 ICC "not otherwise specified" and WHO "defined by differentiation" AML category sizes shrank when compared with that in WHO 2016 (24.1% and 26.8% respectively, vs 38.7%), particularly because of an expansion of the myelodysplasia (MDS)-related group. Of 397 patients with a MDS-related AML according to the ICC, 55.9% were defined by the presence of a MDS-related karyotype. The overall restratification between ELN 2017 and ELN 2022 was 12.9%. The 2022 AML classifications led to a significant improvement of diagnostic schemes. In the real-world setting, conventional cytogenetics, usually rapidly available and less expensive than molecular characterization, stratified 56% of secondary AML, still maintaining a powerful diagnostic role. Considering the similarities between WHO and ICC diagnostic schemes, a tentative scheme to generate a unified model is desirable.
| S-EPMC10477447 | biostudies-literature
Project description:The chronic lymphocytic leukemia International Prognostic Index (CLL-IPI) combines 5 parameters (age, clinical stage, TP53 status [normal vs. del(17p) and/or TP53 mutation], IGHV mutational status, serum β2-microglobulin) to predict survival and time-to-first-treatment (TTFT) in CLL patients. We performed an observational study in 337 prospectively collected, Binet stage A patients to validate the ability of the CLL-IPI to predict TTFT in an independent cohort of early stage CLL patients. The CLL-IPI score stratified Binet stage A patients into three subgroups with different outcome. Since the CLL-IPI was originally developed to predict survival, we next investigated the optimal cut-off score to predict TTFT in Binet stage A patients. Recursive partitioning analysis identified three subsets with scores of 0 (n = 139), 1 (n = 90), and ≥ 2(n = 108). The probability of remaining free from therapy 5 years after diagnosis was 85%, 67% and 46% in these three categories (P < 0.0001.; C-statistic:c = 0.72; 95% CI:0.58-0.81). This optimized CLL-IPI scoring for TTFT was subsequently validated in an independent cohort of Binet A patients from the Mayo Clinic (n = 525). The ability of either original or optimized CLL-IPI to predict TTFT was equivalent to other prognostic models specifically designed for this endpoint (2011 MDACC score and O-CLL1 score). Although originally developed to predict suvival, the CLL-IPI is useful for predicting TTFT in early stage CLL patients. Am. J. Hematol. 91:1090-1095, 2016. © 2016 Wiley Periodicals, Inc.
| S-EPMC5072993 | biostudies-literature