A west African ancestry-associated SNP on 8q24 predicts a positive biopsy in African American men with suspected prostate cancer following PSA screening.

BACKGROUND: African American (AA) men have the highest incidence and mortality rates of prostate cancer (PCa) among all racial groups in the United States. While race is a social construct, for AA men, this overlaps with west African ancestry. Many of the PCa susceptibility variants exhibit distinct allele frequencies and risk estimates across different races and contribute substantially to the large disparities of PCa incidence among races. We previously reported that a single-nucleotide polymorphism (SNP) in 8q24, rs7824364, was strongly associated with west African ancestry and increased risks of PCa in both AA and Puerto Rican men. In this study, we determined whether this SNP can predict biopsy positivity and detection of clinically significant disease (Gleason score [GS] ≥ 7) in a cohort of AA men with suspected PCa. METHODS: SNP rs7824364 was genotyped in 199 AA men with elevated total prostate-specific antigen (PSA) (>2.5 ng/mL) or abnormal digital rectal exam (DRE) and the associations of different genotypes with biopsy positivity and clinically significant disease were analyzed. RESULTS: The variant allele carriers were significantly over-represented in the biopsy-positive group compared to the biopsy-negative group (44% vs. 25.7%, p = 0.011). In the multivariate logistic regression analyses, variant allele carriers were at a more than a twofold increased risk of a positive biopsy (odds ratio [OR] = 2.14, 95% confidence interval [CI] = 1.06-4.32). Moreover, the variant allele was a predictor (OR = 2.26, 95% CI = 1.06-4.84) of a positive biopsy in the subgroup of patients with PSA < 10 ng/mL and normal DRE. The variant allele carriers were also more prevalent in cases with GS ≥ 7 compared to cases with GS < 7 and benign biopsy. CONCLUSIONS: This study demonstrated that the west African ancestry-specific SNP rs7824364 on 8q24 independently predicted a positive prostate biopsy in AA men who were candidates for prostate biopsy subsequent to PCa screening.

Phase 1/2 study of CPX-351 for patients with Int-2 or high risk International Prognostic Scoring System myelodysplastic syndromes and chronic myelomonocytic leukaemia after failure to hypomethylating agents.

Failure after hypomethylating agents (HMAs) is associated with dismal outcomes in higher risk myelodysplastic syndromes (HR-MDS) or chronic myelomonocytic leukaemia (CMML). We aimed to evaluate the safety and preliminary activity of lower doses of CPX-351, a liposomal encapsulation of cytarabine and daunorubicin, in a single-centre, phase 1/2 study for patients with HR-MDS or CMML after HMA failure. Four doses of CPX-351 (10, 25, 50 and 75 units/m2 ) administered on Days 1, 3 and 5 of induction and Days 1 and 3 of consolidation were evaluated. Between June 2019 and June 2023, 25 patients were enrolled (phase 1: n = 15; phase 2: n = 10) including 19 (76%) with HR-MDS and 6 (24%) with CMML. Most common grade 3-4 non-haematological treatment-emergent adverse events were febrile neutropenia (n = 12, 48%) and lung infection (n = 5, 20%). Three patients (age >75) experienced cardiac toxicity at the 75 units/m2 dose. Further enrolment continued at 50 units/m2 . Four- and 8-week mortality were 0% and 8% respectively. The overall response rate was 56% with median relapse-free and overall survivals of 9.2 (95% CI 3.2-15.1 months) and 8.7 months (95% CI 1.8-15.6 months) respectively. These data suggest that lower doses of CPX-351 are safe. Further studies are needed to evaluate its activity.

Analysis of Breast Cancer Mortality in the US-1975 to 2019.

Importance: Breast cancer mortality in the US declined between 1975 and 2019. The association of changes in metastatic breast cancer treatment with improved breast cancer mortality is unclear. Objective: To simulate the relative associations of breast cancer screening, treatment of stage I to III breast cancer, and treatment of metastatic breast cancer with improved breast cancer mortality. Design, Setting, and Participants: Using aggregated observational and clinical trial data on the dissemination and effects of screening and treatment, 4 Cancer Intervention and Surveillance Modeling Network (CISNET) models simulated US breast cancer mortality rates. Death due to breast cancer, overall and by estrogen receptor and ERBB2 (formerly HER2) status, among women aged 30 to 79 years in the US from 1975 to 2019 was simulated. Exposures: Screening mammography, treatment of stage I to III breast cancer, and treatment of metastatic breast cancer. Main Outcomes and Measures: Model-estimated age-adjusted breast cancer mortality rate associated with screening, stage I to III treatment, and metastatic treatment relative to the absence of these exposures was assessed, as was model-estimated median survival after breast cancer metastatic recurrence. Results: The breast cancer mortality rate in the US (age adjusted) was 48/100 000 women in 1975 and 27/100 000 women in 2019. In 2019, the combination of screening, stage I to III treatment, and metastatic treatment was associated with a 58% reduction (model range, 55%-61%) in breast cancer mortality. Of this reduction, 29% (model range, 19%-33%) was associated with treatment of metastatic breast cancer, 47% (model range, 35%-60%) with treatment of stage I to III breast cancer, and 25% (model range, 21%-33%) with mammography screening. Based on simulations, the greatest change in survival after metastatic recurrence occurred between 2000 and 2019, from 1.9 years (model range, 1.0-2.7 years) to 3.2 years (model range, 2.0-4.9 years). Median survival for estrogen receptor (ER)-positive/ERBB2-positive breast cancer improved by 2.5 years (model range, 2.0-3.4 years), whereas median survival for ER-/ERBB2- breast cancer improved by 0.5 years (model range, 0.3-0.8 years). Conclusions and Relevance: According to 4 simulation models, breast cancer screening and treatment in 2019 were associated with a 58% reduction in US breast cancer mortality compared with interventions in 1975. Simulations suggested that treatment for stage I to III breast cancer was associated with approximately 47% of the mortality reduction, whereas treatment for metastatic breast cancer was associated with 29% of the reduction and screening with 25% of the reduction.

Collaborative Modeling to Compare Different Breast Cancer Screening Strategies: A Decision Analysis for the US Preventive Services Task Force.

Importance: The effects of breast cancer incidence changes and advances in screening and treatment on outcomes of different screening strategies are not well known. Objective: To estimate outcomes of various mammography screening strategies. Design, Setting, and Population: Comparison of outcomes using 6 Cancer Intervention and Surveillance Modeling Network (CISNET) models and national data on breast cancer incidence, mammography performance, treatment effects, and other-cause mortality in US women without previous cancer diagnoses. Exposures: Thirty-six screening strategies with varying start ages (40, 45, 50 years) and stop ages (74, 79 years) with digital mammography or digital breast tomosynthesis (DBT) annually, biennially, or a combination of intervals. Strategies were evaluated for all women and for Black women, assuming 100% screening adherence and "real-world" treatment. Main Outcomes and Measures: Estimated lifetime benefits (breast cancer deaths averted, percent reduction in breast cancer mortality, life-years gained), harms (false-positive recalls, benign biopsies, overdiagnosis), and number of mammograms per 1000 women. Results: Biennial screening with DBT starting at age 40, 45, or 50 years until age 74 years averted a median of 8.2, 7.5, or 6.7 breast cancer deaths per 1000 women screened, respectively, vs no screening. Biennial DBT screening at age 40 to 74 years (vs no screening) was associated with a 30.0% breast cancer mortality reduction, 1376 false-positive recalls, and 14 overdiagnosed cases per 1000 women screened. Digital mammography screening benefits were similar to those for DBT but had more false-positive recalls. Annual screening increased benefits but resulted in more false-positive recalls and overdiagnosed cases. Benefit-to-harm ratios of continuing screening until age 79 years were similar or superior to stopping at age 74. In all strategies, women with higher-than-average breast cancer risk, higher breast density, and lower comorbidity level experienced greater screening benefits than other groups. Annual screening of Black women from age 40 to 49 years with biennial screening thereafter reduced breast cancer mortality disparities while maintaining similar benefit-to-harm trade-offs as for all women. Conclusions: This modeling analysis suggests that biennial mammography screening starting at age 40 years reduces breast cancer mortality and increases life-years gained per mammogram. More intensive screening for women with greater risk of breast cancer diagnosis or death can maintain similar benefit-to-harm trade-offs and reduce mortality disparities.

CondiS web app: imputation of censored lifetimes for machine learning-based survival analysis.

SUMMARY: In the era of big data, machine learning techniques are widely applied to every area in biomedical research including survival analysis. It is well recognized that censoring, which is a common missing issue in survival time data, hampers the direct usage of these machine learning techniques. Here, we present CondiS, a web toolkit with graphical user interface to help impute the survival times for censored observations and predict the survival times for future enrolled patients. CondiS imputes a censored survival time based on its distribution conditional on its observed part. When covariates are available, CondiS-X incorporates this information to further increase the imputation accuracy. Users can also upload data of newly enrolled patients and predict their survival times. As the first web-app tool with an imputation function for censored lifetime data, CondiS web can facilitate conducting survival analysis with machine learning approaches. AVAILABILITY AND IMPLEMENTATION: CondiS is an open-source application implemented with Shiny in R, available free at: https://biostatistics.mdanderson.org/shinyapps/CondiS/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Frontline combination of ponatinib and hyper-CVAD in Philadelphia chromosome-positive acute lymphoblastic leukemia: 80-months follow-up results.

The combination of ponatinib, a third-generation BCR::ABL1 tyrosine kinase inhibitor, with hyper-CVAD chemotherapy resulted in high rates of complete molecular remissions and survival, without the need for stem cell transplantation (SCT) in most patients with Philadelphia chromosome(Ph)-positive acute lymphocytic leukemia (ALL). Confirming these results in a large cohort of patients with longer follow-up would establish this regimen as a new standard of care. Adults with newly diagnosed Ph-positive ALL were treated with the hyper-CVAD regimen. Ponatinib was added as 45 mg daily × 14 during induction, then 45 mg daily continuously (first 37 patients) or 30 mg daily continuously, with dose reduction to 15 mg daily upon achievement of a complete molecular response (CMR; absence of a detectable BCR::ABL1 transcript by quantitative reverse transcription polymerase-chain reaction at a sensitivity of 0.01%). Maintenance therapy consisted of daily ponatinib and vincristine-prednisone monthly for 2 years, followed by daily ponatinib indefinitely. Twelve intrathecal injections of cytarabine alternating with methotrexate were given as central nervous system prophylaxis. The trial is registered on clinicaltrials.gov with the identifier NCT01424982. Eighty-six patients were treated. Their median age was 46 years (range, 21-80). All 68 patients with active disease at the initiation of therapy achieved complete response (CR) The cumulative CMR rate was 86%. Twenty- patients (23%) underwent allogeneic SCT. With a median follow-up of 80 months (range, 16-129 months), the estimated 6-year event-free survival rate was 65% and the overall survival rate was 75%. There was no difference in outcome by performance of allogeneic SCT in first CR. Common grade 3-5 adverse events included infection (n = 80, 93%), increased liver transaminases (n = 26, 31%) and total bilirubin (n = 13, 15%), hypertension (n = 15, 17%), pancreatitis (n = 13, 15%), hemorrhage (n = 12, 13%), and skin rash (n = 9, 10%). Two ponatinib-related deaths from myocardial infarction (3%; at months 2.6 and 4.3, respectively; both in CR) in the first 37 patients treated led to the ponatinib dose-modifications mentioned earlier, with no further ponatinib-related deaths observed. The long-term results of ponatinib and hyper-CVAD continue to demonstrate excellent outcome results and acceptable safety data, indicating that this strategy is another standard of care approach in frontline Ph-positive ALL.

An NTS-CeA projection modulates depression-like behaviors in a mouse model of chronic pain.

Depressive symptoms comorbid with chronic pain are a common health problem, but the underlying neural circuit mechanisms remain elusive. Here, we identify a glutamatergic projection from the nucleus of the solitary tract (NTS) to the central nucleus of the amygdala (CeA) that mediates depression-like behaviors in a chemotherapy-induced neuropathic pain model. Inhibition or ablation of the glutamatergic NTS neurons alleviates depressive but not hypersensitive behaviors in these mice. The projected neurons form excitatory synapses with somatostatin-expressing neurons in the CeA. Silencing the NTS-CeA projection alleviates depressive but not hypersensitive behaviors, whereas activating the proection promotes depressive behaviors. In addition, in naïve mice, activation of the NTS-CeA projection induces obvious depressive behaviors that can be blocked by silencing the CeA somatostatin-expressing neurons. Together, we reveal a modulatory role of the NTS and its glutamatergic projection to the CeA circuit in modulating depression-like behaviors comorbid to chronic pain.

Reflecting on 20 years of breast cancer modeling in CISNET: Recommendations for future cancer systems modeling efforts.

Since 2000, the National Cancer Institute's Cancer Intervention and Surveillance Modeling Network (CISNET) modeling teams have developed and applied microsimulation and statistical models of breast cancer. Here, we illustrate the use of collaborative breast cancer multilevel systems modeling in CISNET to demonstrate the flexibility of systems modeling to address important clinical and policy-relevant questions. Challenges and opportunities of future systems modeling are also summarized. The 6 CISNET breast cancer models embody the key features of systems modeling by incorporating numerous data sources and reflecting tumor, person, and health system factors that change over time and interact to affect the burden of breast cancer. Multidisciplinary modeling teams have explored alternative representations of breast cancer to reveal insights into breast cancer natural history, including the role of overdiagnosis and race differences in tumor characteristics. The models have been used to compare strategies for improving the balance of benefits and harms of breast cancer screening based on personal risk factors, including age, breast density, polygenic risk, and history of Down syndrome or a history of childhood cancer. The models have also provided evidence to support the delivery of care by simulating outcomes following clinical decisions about breast cancer treatment and estimating the relative impact of screening and treatment on the United States population. The insights provided by the CISNET breast cancer multilevel modeling efforts have informed policy and clinical guidelines. The 20 years of CISNET modeling experience has highlighted opportunities and challenges to expanding the impact of systems modeling. Moving forward, CISNET research will continue to use systems modeling to address cancer control issues, including modeling structural inequities affecting racial disparities in the burden of breast cancer. Future work will also leverage the lessons from team science, expand resource sharing, and foster the careers of early stage modeling scientists to ensure the sustainability of these efforts.

A flexible-hazards cure model with application to patients with soft tissue sarcoma.

In medical research, it is often of great interest to have an accurate estimation of cure rates by different treatment options and for different patient groups. If the follow-up time is sufficiently long and the sample size is large, the proportion of cured patients will make the Kaplan-Meier estimator of survival function have a flat plateau at its tail, whose value indicates the overall cure rate. However, it may be difficult to estimate and compare the cure rates for all the subsets of interest in this way, due to the limit of sample sizes and curse of dimensionality. In the current literature, most regression models for estimating cure rates assume proportional hazards (PH) between different subgroups. It turns out that the estimation of cure rates for subgroups is highly sensitive to this assumption, so more flexible models are needed, especially when this PH assumption is clearly violated. We propose a new cure model to simultaneously incorporate both PH and non-PH scenarios for different covariates. We develop a stable and easily implementable iterative procedure for parameter estimation through maximization of the nonparametric likelihood function. The covariance matrix is estimated by adding perturbation weights to the estimation procedure. In simulation studies, the proposed method provides unbiased estimation for the regression coefficients, survival curves, and cure rates given covariates, while existing models are biased. Our model is applied to a study of stage III soft tissue sarcoma and provides trustworthy estimation of cure rates for different treatment and demographic groups.

CondiS: A conditional survival distribution-based method for censored data imputation overcoming the hurdle in machine learning-based survival analysis.

Data analyses by machine learning (ML) algorithms are gaining popularity in biomedical research. When time-to-event data are of interest, censoring is common and needs to be properly addressed. Most ML methods cannot conveniently and appropriately take the censoring information into consideration, potentially leading to inaccurate or biased results. We aim to develop a general-purpose method for imputing censored survival data, facilitating downstream ML analysis. In this study, we propose a novel method of imputing the survival times for censored observations. The proposal is based on their conditional survival distributions (CondiS) derived from Kaplan-Meier estimators. CondiS can replace censored observations with their best approximations from the statistical model, allowing for direct application of ML methods. When covariates are available, we extend CondiS by incorporating the covariate information through ML modeling (CondiS-X), which further improves the accuracy of the imputed survival time. Compared with existing methods with similar purposes, the proposed methods achieved smaller prediction errors and higher concordance with the underlying true survival times in extensive simulation studies. We also demonstrated the usage and advantages of the proposed methods through two real-world cancer datasets. The major advantage of CondiS is that it allows for the direct application of standard ML techniques for analysis once the censored survival times are imputed. We present a user-friendly R package to implement our method, which is a useful tool for ML-based biomedical research in this era of big data.

Isavuconazole as Primary Antifungal Prophylaxis in Patients With Acute Myeloid Leukemia or Myelodysplastic Syndrome: An Open-label, Prospective, Phase 2 Study.

BACKGROUND: Mold-active primary antifungal prophylaxis (PAP) is routinely recommended in neutropenic patients with newly diagnosed acute myeloid leukemia (AML) or high-risk myelodysplastic syndrome (MDS) undergoing remission-induction chemotherapy (RIC). Isavuconazole (ISAV) is an extended spectrum mold-active triazole and has superior tolerability and fewer significant drug-drug interactions compared with other triazoles. METHODS: In our investigator-initiated, phase 2 trial, treatment-naive adult patients with AML or MDS starting RIC received ISAV per the dosing recommendations in the US label until neutrophil recovery (absolute neutrophil count [ANC] ≥ 0.5 × 109/L) and attainment of complete remission, occurrence of invasive fungal infection (IFI), or for a maximum of 12 weeks. The primary endpoint was the incidence of proven/probable IFI during ISAV PAP and up to 30 days after the last dose. RESULTS: Sixty-five of 75 enrolled patients received ISAV PAP (median age, 67 years, median ANC at enrollment, 0.72 × 109/L). Thirty-two patients (49%) received oral targeted leukemia treatments (venetoclax, FTL3 inhibitors). Including the 30-day follow-up period, probable/proven and possible IFIs were encountered in 4 (6%) and 8 patients (12%), respectively. ISAV trough serum concentrations were consistently > 1 µg/mL, showed low intraindividual variation, and were not significantly influenced by chemotherapy regimen. Tolerability of ISAV was excellent, with only 3 cases (5%) of mild to moderate elevations of liver function tests and no QTc prolongations. CONCLUSIONS: ISAV is a safe and effective alternative for PAP in patients with newly diagnosed AML/MDS undergoing RIC in the era of recently approved or emerging small-molecule antileukemia therapies. CLINICAL TRIALS REGISTRATION: NCT03019939.

Long-term follow-up of salvage therapy using a combination of inotuzumab ozogamicin and mini-hyper-CVD with or without blinatumomab in relapsed/refractory Philadelphia chromosome-negative acute lymphoblastic leukemia.

BACKGROUND: The outcome of patients with relapsed/refractory (R/R) acute lymphoblastic leukemia (ALL) is poor. The combination of inotuzumab with low-intensity mini-hyper-CVD (mini-hyper-CVD; cyclophosphamide and dexamethasone at 50% dose reduction, no anthracycline, methotrexate at 75% dose reduction, cytarabine at 0.5 g/m2 × 4 doses) chemotherapy has shown encouraging results. The sequential addition of blinatumomab might improve outcome in patients with R/R ALL. METHODS: We used lower intensity chemotherapy, mini-hyper-CVD (cyclophosphamide and dexamethasone at 50% dose reduction, no anthracycline, methotrexate at 75% dose reduction, cytarabine at 0.5 g/m2 x 4 doses) compared to conventional hyper-CVAD. RESULTS: Ninety-six patients with a median age of 37 years (range, 18-87 years) were treated. Overall, 77 patients (80%) responded, 55 (57%) of whom achieved complete response. The overall measurable residual disease negativity rate among responders was 83%. Forty-four (46%) patients underwent later allogeneic stem cell transplantation. Veno-occlusive disease of any grade occurred in 10 (10%) patients. The rates were 13% with the original schedule and 3% with the use of lower-dose inotuzumab and sequential blinatumomab. With a median follow-up of 36 months, the median overall survival (OS) was 13.4 months, with 3-year OS rates of 33%. The 3-year OS rate for patients with CD22 expression ≥70% and without adverse cytogenetics (KMT2A rearrangements, low hypodiploidy/near triploidy) was 55%. CONCLUSION: The combination of inotuzumab and low-intensity mini-hyper-CVD chemotherapy with or without blinatumomab shows sustained efficacy in patients with R/R ALL.

Phase II study of azacitidine with pembrolizumab in patients with intermediate-1 or higher-risk myelodysplastic syndrome.

Programmed cell death protein 1 (PD-1) and PD-ligand 1 (PD-L1) expression is upregulated in cluster of differentiation 34 (CD34)+ bone marrow cells from patients with myelodysplastic syndromes (MDS). Hypomethylating agent (HMA) treatment results in further increased expression of these immune checkpoints. We hypothesised that combining an anti-PD-1 antibody with HMAs may have efficacy in patients with MDS. To test this concept, we designed a phase II trial of the combination of azacitidine and pembrolizumab with two cohorts. In the 17 previously untreated patients, the overall response rate (ORR) was 76%, with a complete response (CR) rate of 18% and median overall survival (mOS) not reached after a median follow-up of 12·8 months. For the HMA-failure cohort (n = 20), the ORR was 25% and CR rate was 5%; with a median follow-up of 6·0 months, the mOS was 5·8 months. The most observed toxicities were pneumonia (32%), arthralgias (24%) and constipation (24%). Immune-related adverse events requiring corticosteroids were required in 43%. Overall, this phase II trial suggests that azacitidine and pembrolizumab is safe with manageable toxicities in patients with higher-risk MDS. This combined therapy may have anti-tumour activity in a subset of patients and merits further studies in the front-line setting.

Downregulation of metallothionein-2 contributes to oxaliplatin-induced neuropathic pain.

BACKGROUND: We previously reported a correlation between small doses of oxaliplatin penetrating onto the spinal cord and acute pain after chemotherapy. Here, we propose that MT2 within the spinal dorsal horns participates in the development of oxaliplatin-induced neuropathic pain and may be a pharmacological target for the prevention and treatment of chemotherapy-induced peripheral neuropathy (CIPN). METHODS: The rat model of CIPN was established by 5 consecutive injections of oxaliplatin (0.4 mg/100 g/day). Genetic restoration of neuron-specific metallothionein-2 was implemented 21 days before oxaliplatin treatment, and also, genetic inhibition by metallothionein-2 siRNA was performed. Mechanical allodynia and locomotor activity were assayed. Cell-specific expression of metallothionein-2, the mRNA levels of pro-inflammatory cytokines, nuclear translocation of NF-κB, the protein levels of expression of IκB-α, and interaction between IκB-α and P65 were evaluated in the spinal dorsal horns. Also, in vitro interaction of sequentially deleted IκB-α promoter with metallothionein-2 was used to assess the signal transduction mechanism. RESULTS: We found that oxaliplatin induced downregulation of metallothionein-2 in rat spinal cord neurons. By contrast, genetic restoration of metallothionein-2 in the spinal dorsal horn neuron blocked and reversed neuropathic pain in oxaliplatin-treated rats of both sexes, whereas genetic inhibition of metallothionein-2 triggered neuropathic pain in normal rats. Overall locomotor activity was not impaired after the genetic alterations of metallothionein-2. At the molecular level, metallothionein-2 modulated oxaliplatin-induced neuroinflammation, activation of NF-κB, and inactive transcriptional expression of IκB-α promoter, and these processes could be blocked by genetic restoration of metallothionein-2 in the spinal dorsal horn neurons. CONCLUSIONS: Metallothionein-2 is a potential target for the prevention and treatment of CIPN. A reduction of NF-κB activation and inflammatory responses by enhancing the transcription of IκB-α promoter is proposed in the mechanism.

Randomized trial of ibrutinib vs ibrutinib plus rituximab in patients with chronic lymphocytic leukemia.

Ibrutinib, an oral covalent inhibitor of Bruton's tyrosine kinase, is an effective therapy for patients with chronic lymphocytic leukemia (CLL). To determine whether rituximab provides added benefit to ibrutinib, we conducted a randomized single-center trial of ibrutinib vs ibrutinib plus rituximab. Patients with CLL requiring therapy were randomized to receive 28-day cycles of once-daily ibrutinib 420 mg, either as a single agent (n = 104), or together with rituximab (375 mg/m2; n = 104), given weekly during cycle 1, then once per cycle until cycle 6. The primary end point was progression-free survival (PFS) in the intention-to-treat population. We enrolled 208 patients with CLL, 181 with relapsed CLL and 27 treatment-naive patients with high-risk disease (17p deletion or TP53 mutation). After a median follow-up of 36 months, the Kaplan-Meier estimates of PFS were 86% (95% confidence interval [CI], 76.6-91.9) for patients receiving ibrutinib, and 86.9% (95% CI, 77.3-92.6) for patients receiving ibrutinib plus rituximab. Similarly, response rates were the same in both arms (overall response rate, 92%). However, time to normalization of peripheral blood lymphocyte counts and time to complete remission were shorter, and residual disease levels in the bone marrow were lower, in patients receiving ibrutinib plus rituximab. We conclude that the addition of rituximab to ibrutinib in relapsed and treatment-naive high-risk patients with CLL failed to show improvement in PFS. However, patients treated with ibrutinib plus rituximab reached their remissions faster and achieved significantly lower residual disease levels. Given these results, ibrutinib as single-agent therapy remains current standard-of-care treatment in CLL. This trial was registered at www.clinicaltrials.gov as #NCT02007044.

On the time-varying predictive performance of longitudinal biomarkers: Measure and estimation.

In many biomedical studies, participants are monitored at periodic visits until the occurrence of the failure event. Biomarkers are often measured repeatedly during these visits, and such measurements can facilitate updated disease prediction. In this work, we propose a two-dimensional incident dynamic area under curve (AUC), to capture the variability due to both the biomarker assessment time and the prediction time to comprehensively quantify the predictive performance of a longitudinal biomarker. We propose a pseudo partial-likelihood to achieve consistent estimation of the AUC under two realistic scenarios of visit schedules. Variance estimation methods are designed to facilitate inferential procedures. We examine the finite-sample performance of our method through extensive simulations. The methods are applied to a study of chronic myeloid leukemia to evaluate the predictive performance of longitudinally collected gene expression levels.

Functional principal component based landmark analysis for the effects of longitudinal cholesterol profiles on the risk of coronary heart disease.

Patients' longitudinal biomarker changing patterns are crucial factors for their disease progression. In this research, we apply functional principal component analysis techniques to extract these changing patterns and use them as predictors in landmark models for dynamic prediction. The time-varying effects of risk factors along a sequence of landmark times are smoothed by a supermodel to borrow information from neighbor time intervals. This results in more stable estimation and more clear demonstration of the time-varying effects. Compared with the traditional landmark analysis, simulation studies show our proposed approach results in lower prediction error rates and higher area under receiver operating characteristic curve (AUC) values, which indicate better ability to discriminate between subjects with different risk levels. We apply our method to data from the Framingham Heart Study, using longitudinal total cholesterol (TC) levels to predict future coronary heart disease (CHD) risk profiles. Our approach not only obtains the overall trend of biomarker-related risk profiles, but also reveals different risk patterns that are not available from the traditional landmark analyses. Our results show that high cholesterol levels during young ages are more harmful than those in old ages. This demonstrates the importance of analyzing the age-dependent effects of TC on CHD risk.

Long-term results of low-intensity chemotherapy with clofarabine or cladribine combined with low-dose cytarabine alternating with decitabine in older patients with newly diagnosed acute myeloid leukemia.

The treatment of older patients with newly diagnosed acute myeloid leukemia (AML) using intensive chemotherapy is associated with treatment intolerance and poor survival. We evaluated two new lower-intensity regimens with clofarabine (n = 119) or cladribine (n = 129) combined with low-dose cytarabine (LDAC) alternating with decitabine. We reviewed response rates by subgroup and long term outcomes of 248 patients with newly diagnosed non core-binding-factor AML treated on two clinical trials investigating double nucleoside-analogue therapy (DNT) alternating with HMA from October, 2008 to April, 2018. Of 248 patients with a median age of 69 years (range, 49-85 years), 102 patients (41%) were ≥ 70 years, and 108 (44%) had adverse karyotype. Overall, 164 patients (66%) responded: 147 (59%) complete remission (CR) and 17 (7%) CR with incomplete count recovery (CRi). With a median follow up of 60 months, median relapse-free and overall survival (OS) were 10.8 and 12.5 months, respectively. The 2-year OS was 29%. Among patients with normal karyotype, the CR/CRi rate was 79% and the median OS 19.9 months. High response rates and OS were observed in patients with mutations in NPM1, FLT3, IDH2, and RUNX1. The 4- and 8-week mortality rates were 2% and 11%, respectively. The backbone of clofarabine or cladribine and LDAC alternating with decitabine was effective and safe for the treatment of older patients with newly diagnosed AML. Incorporating targeted therapies could extend the efficacy of this approach and provide more curative therapeutic options in this AML population.

A pilot study of lower doses of ibrutinib in patients with chronic lymphocytic leukemia.

Ibrutinib is highly efficacious and used at 420 mg/d for treatment of chronic lymphocytic leukemia (CLL). We previously demonstrated a decline in Bruton's tyrosine kinase (BTK) protein levels in CLL cells after 1 cycle of ibrutinib, suggesting ibrutinib dose could be lowered after the first cycle without loss of biological effect. To test this postulate, a pilot study (NCT02801578) was designed to systematically reduce ibrutinib dosing within the same patient with CLL over the course of three 28-day cycles. After an initial cycle of 420 mg/d, the dose was reduced to 280 mg/d in cycle 2, and then to 140 mg/d in cycle 3. Eleven patients began study treatment, and 9 completed the 3 cycles. Plasma and intracellular pharmacokinetics (PK), BTK occupancy, and pharmacodynamic (PD) response at different doses of ibrutinib were compared. Plasma and intracellular levels of ibrutinib were dose-dependent, and even the lowest dose was sufficient to occupy, on average, more than 95% of BTK protein. In concert, BTK downstream signaling inhibition was maintained with 140 mg/d ibrutinib in cycle 3, and there were comparable reductions in total and phospho-BTK (Tyr223) protein levels across 3 cycles. Reductions of plasma chemokine CCL3 and CCL4 levels, considered to be biomarkers of ibrutinib response, were similar during the 3 cycles. These PK/PD data demonstrate that after 1 cycle of ibrutinib at the standard 420 mg/d dose, the dose can be reduced without losing biological activity. Clinical efficacy of lower doses needs to be systematically evaluated. Such dose reductions would lower drug cost, lessen untoward toxicity, and facilitate rationale-based combinations. This trial was registered at www.clinicaltrials.gov as #NCT02801578.

Semiparametric modelling and estimation of covariate-adjusted dependence between bivariate recurrent events.

A time-dependent measure, termed the rate ratio, was proposed to assess the local dependence between two types of recurrent event processes in one-sample settings. However, the one-sample work does not consider modeling the dependence by covariates such as subject characteristics and treatments received. The focus of this paper is to understand how and in what magnitude the covariates influence the dependence strength for bivariate recurrent events. We propose the covariate-adjusted rate ratio, a measure of covariate-adjusted dependence. We propose a semiparametric regression model for jointly modeling the frequency and dependence of bivariate recurrent events: the first level is a proportional rates model for the marginal rates and the second level is a proportional rate ratio model for the dependence structure. We develop a pseudo-partial likelihood to estimate the parameters in the proportional rate ratio model. We establish the asymptotic properties of the estimators and evaluate the finite sample performance via simulation studies. We illustrate the proposed models and methods using a soft tissue sarcoma study that examines the effects of initial treatments on the marginal frequencies of local/distant sarcoma recurrence and the dependence structure between the two types of cancer recurrence.