BACKGROUND: The annual incidence of chronic myeloid leukemia (CML) in the United States is approximately 4800 cases. With the success of tyrosine kinase inhibitor (TKI) therapy, the all‐cause annual mortality rate was reduced to 2%. Therefore, the prevalence of CML is increasing over time. Estimating the CML prevalence and plateau prevalence is important in the implementation of health care strategies and future therapeutic trials. The objective of this report was to estimate the increasing prevalence and plateau prevalence of CML in future years.METHODS: The prevalence of CML was estimated based on several parameters: the annual mortality rate on TKI therapy compared with a age‐matched, normal population; the incidence of CML; the anticipated population growth in the United States; and aging of the population.RESULTS: On the basis of these calculations, the mortality ratio of patients with CML compared with an age‐matched normal population was approximately 1.53. The estimated prevalence of CML is approximately 70,000 in 2010, 112,000 in 2020, 144,000 in 2030, 167,000 in 2040, and 181,000 in 2050, when it will reach a near plateau prevalence.CONCLUSIONS: The current results indicated that the prevalence of CML will continue to increase to reach a near plateau prevalence 35 times the annual incidence. These estimates should be considered in health care policies and in the design of future studies in CML. Cancer 2012;118: 3123–27. © 2012 American Cancer Society.

PURPOSE: Azacitidine plus venetoclax is a standard of care for patients with newly diagnosed AML who are unfit for intensive chemotherapy. However, FLT3 mutations are a common mechanism of resistance to this regimen. The addition of gilteritinib, an oral FLT3 inhibitor, to azacitidine and venetoclax may improve outcomes in patients with FLT3-mutated AML. METHODS: This phase I/II study evaluated azacitidine, venetoclax, and gilteritinib in two cohorts: patients with (1) newly diagnosed FLT3-mutated AML who were unfit for intensive chemotherapy or (2) relapsed/refractory FLT3-mutated AML (ClinicalTrials.gov identifier: NCT04140487 ). The primary end points were the maximum tolerated dose of gilteritinib (phase I) and the combined complete remission (CR)/CR with incomplete hematologic recovery (CRi) rate (phase II). RESULTS: Fifty-two patients were enrolled (frontline [n = 30]; relapsed/refractory [n = 22]). The recommended phase II dose was gilteritinib 80 mg once daily in combination with azacitidine and venetoclax. In the frontline cohort, the median age was 71 years and 73% of patients had an FLT3-internal tandem duplication (ITD) mutation. The CR/CRi rate was 96% (CR, 90%; CRi, 6%). Sixty-five percent of evaluable patients achieved FLT3-ITD measurable residual disease <5 × 10^–5 within four cycles. With a median follow-up of 19.3 months, the median relapse-free survival (RFS) and overall survival (OS) have not been reached and the 18-month RFS and OS rates are 71% and 72%, respectively. In the relapsed/refractory cohort, the CR/CRi rate was 27%; nine additional patients (41%) achieved a morphologic leukemia–free state. The most common grade 3 or higher nonhematologic adverse events were infection (62%) and febrile neutropenia (38%), which were more frequent in the relapsed/refractory cohort. CONCLUSION: The combination of azacitidine, venetoclax, and gilteritinib resulted in high rates of CR/CRi, deep FLT3 molecular responses, and encouraging survival in newly diagnosed FLT3-mutated AML. Myelosuppression was manageable with mitigative dosing strategies.

Measurable residual disease (MRD) is highly prognostic for relapse and overall survival (OS) in acute lymphoblastic leukemia (ALL), although many patients with apparent “MRD negativity” by standard assays still relapse. We evaluated the clinical impact of a highly sensitive next-generation sequencing (NGS) MRD assay in 74 adults with ALL undergoing frontline therapy. Among remission samples that were MRD negative by multiparameter flow cytometry (MFC), 46% were MRD+ by the NGS assay. After 1 cycle of induction chemotherapy, MRD negativity by MFC at a sensitivity of 1 × 10−4 and NGS at a sensitivity of 1 × 10−6 was achieved in 66% and 23% of patients, respectively. The 5-year cumulative incidence of relapse (CIR) among patients who achieved MRD negativity by MFC at complete remission (CR) was 29%; in contrast, no patients who achieved early MRD negativity by NGS relapsed, and their 5-year OS was 90%. NGS MRD negativity at CR was associated with significantly decreased risk of relapse compared with MRD positivity (5-year CIR, 0% vs 45%, respectively; P = .04). Among patients who were MRD negative by MFC, detection of low levels of MRD by NGS identified patients who still had a significant risk of relapse (5-year CIR, 39%). Early assessment of MRD using a highly sensitive NGS assay adds clinically relevant prognostic information to standard MFC-based approaches and can identify patients with ALL undergoing frontline therapy who have a very low risk of relapse and excellent long-term survival.

Quantitative real-time polymerase chain reaction (qPCR) is a sensitive gene quantification method that has been extensively used in biological and biomedical fields. The currently used methods for PCR data analysis, including the threshold cycle method and linear and nonlinear model-fitting methods, all require subtracting background fluorescence. However, the removal of background fluorescence can hardly be accurate and therefore can distort results. We propose a new method, the taking-difference linear regression method, to overcome this limitation. Briefly, for each two consecutive PCR cycles, we subtract the fluorescence in the former cycle from that in the latter cycle, transforming the n cycle raw data into n −1 cycle data. Then, linear regression is applied to the natural logarithm of the transformed data. Finally, PCR amplification efficiencies and the initial DNA molecular numbers are calculated for each reaction. This taking-difference method avoids the error in subtracting an unknown background, and thus it is more accurate and reliable. This method is easy to perform, and this strategy can be extended to all current methods for PCR data analysis.