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Response Rates as Predictors of Overall Survival: A Meta-Analysis of Acute Myeloid Leukemia Trials.

ABSTRACT: Background: Response rates such as overall response rate (ORR), complete response (CR) and complete response with incomplete blood recovery (CRi) can be evaluated in a much shorter period of time than overall survival (OS), potentially accelerating decision making during drug development. The objective of this work was to evaluate the relationship between ORR, CR, CRi or better (CRi+CR) rates and median OS to determine whether response rates could be used as predictors of median OS in acute myeloid leukemia (AML). Methods: A review of published literature was conducted to identify relevant AML clinical trials. Weighted linear regression was performed with various linearizing transformations of response rates and median OS. Covariates of interest were evaluated using a forward inclusion, backward elimination covariate model building procedure at α=0.01 and α=0.005, respectively. Results: Twenty trials involving 26 cohorts were included in the meta-analysis. Azactidine treatment was a significant predictor with longer OS compared to decitabine or low dose cytarabine for a given response rate (P < 0.005). Linear regression analysis indicated that the correlation of both CRi or better rates and CR rates with median OS was higher than that of ORR with median OS. The final model showed a strong correlation between CRi or better rates and median OS (R2=0.66). Conclusion: Significant correlation between CRi or better rates and median OS in AML highlights the potential for CRi or better rate, in addition to CR rate, to serve as surrogate markers for median OS.

SUBMITTER: Agarwal SK

PROVIDER: S-EPMC5535711 | biostudies-other | 2017

REPOSITORIES: biostudies-other

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Project description:BACKGROUND:Aberrant DNA methylation is known to occur in patients with acute myeloid leukemia (AML), whereas methylation signatures and prognostic markers have been proposed. The objective of the current study was to evaluate all CpG sites of the genome and identify prognostic methylation markers for overall survival in patients with AML with normal karyotype (AML-NK). METHODS:AML-NK samples from 7 SWOG trials were analyzed using a novel genome-wide approach called "CHARMcox" (comprehensive high-throughput array-based relative methylation analysis combined with the Cox proportional hazards model) controlling for known clinical covariates. CHARMcox was applied to a phase 1 discovery cohort (72 patients) to identify survival-associated methylation regions (SAMRs). Subsequently, using bisulfite pyrosequencing, SAMRs were studied in phase 2 model-building (65 patients) and phase 3 validation (65 patients) cohorts. An independent external cohort from The Cancer Genome Atlas (TCGA) AML study (LAML) was used for further validation (93 patients). RESULTS:Two SAMRs, located at the CpG island shores of leucine zipper tumor suppressor 2 (LZTS2) and nuclear receptor subfamily 6 group a member 1 (NR6A1), respectively, were identified. Multivariable analyses demonstrated that hypomethylation of either LZTS2 or NR6A1 was associated with worse overall survival in the SWOG cohort (P<.001). The prognosis was validated in patients with AML-NK from the TCGA-LAML cohort. Methylation values below the median at both markers predicted worse overall survival (SWOG: hazard ratio, 1.89 [P<.001]; and TCGA-LAML: hazard ratio, 2.08 [P=.006]). The C-statistic was 0.71 for both cohorts, and the impact was independent of the Fms-related tyrosine kinase 3 internal tandem duplication (FLT3-ITD) status. CONCLUSIONS:The 2 methylation markers, measurable by clinically applicable assays such as bisulfite pyrosequencing, are promising for risk stratification among patients with AML-NK. Cancer 2017;123:2472-81. © 2017 American Cancer Society.

Project description:BackgroundAcute myeloid leukemia (AML) is one of the most common hematological malignancies and accounts for about 20% of childhood leukemias. Currently, immunotherapy is one of the recommended treatment schemes for recurrent AML patients to improve their survival rates. Nonetheless, low remission and high mortality rates are observed in recurrent AML and challenge the prognosis of AML patients. To address this problem, we aimed to establish and verify a reliable prognostic risk model using immune-related genes to improve the prognostic evaluation and recommendation for personalized treatment of AML.MethodsTranscriptome data and clinical data were acquired from the TARGET database while immune genes were sourced from InnateDB and ImmPort Shared databases. The mRNA expression profile matrix of immune genes from 62 normal samples and 1408 AML cases was extracted from the transcriptome data and subjected to differential expression (DE) analysis. The entire cohort of DE immune genes was randomly divided into the test group and training group. The prognostic model associated with immune genes was constructed using the training group. The test group and entire cohort were employed for model validation. Lastly, we analyzed the potential clinical application of the model and its association with immune cell infiltration.ResultsIn total, 751 DE immune genes were differentially regulated, including 552 upregulated and 199 downregulated. Based on these DE genes, we developed and validated a prognostic risk model composed of seven immune genes, GDF1, TPM2, IL1R1, PSMD4, IL5RA, DHCR24, and IL12RB2. This model is able to predict the 5-year survival rate more accurately compared with age, gender, and risk stratification. Further analysis showed that CD8+ T-cell contents and neutrophil infiltration decreased but macrophage infiltration increased as the risk score increased.ConclusionsA seven-immune gene model of AML was developed and validated. We propose this model as an independent prognostic variable able to estimate the 5-year survival rate. In addition, the model can also reflect the immune microenvironment of AML patients.

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Response Rates as Predictors of Overall Survival: A Meta-Analysis of Acute Myeloid Leukemia Trials.

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