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1.
Artigo em Inglês | MEDLINE | ID: mdl-34805718

RESUMO

PURPOSE: Novel Bayesian adaptive designs provide an effective way to improve clinical trial efficiency. These designs are superior to conventional methods, but implementing them can be challenging. The aim of this article was to describe what we learned while applying a novel Bayesian phase I-II design in a recent trial. METHODS: The primary goal of the trial was to optimize radiation therapy (RT) dose among three levels (low, standard, and high), given either with placebo (P) or an investigational agent (A), for treating locally advanced, radiation-naive pancreatic cancer, deemed appropriate for RT rather than surgery. Up to 48 patients were randomly assigned fairly between RT plus P and RT plus A, with RT dose-finding done within each arm using the late-onset efficacy-toxicity design on the basis of two coprimary end points, tumor response and dose-limiting toxicity, both evaluated at up to 90 days. The random assignment was blinded, but within each arm, unblinded RT doses were chosen adaptively using software developed within the institution. RESULTS: Implementing the design involved double-blind balance-restricted random assignment, real-time assessment of patient outcomes to evaluate the efficacy-toxicity trade-off for each RT dose in each arm to optimize each patient's RT dose adaptively, and transition from a single-center trial to a multicenter trial. We present lessons learned and illustrative documentation. CONCLUSION: Implementing novel Bayesian adaptive trial designs requires close collaborations between physicians, pharmacists, statisticians, data managers, and sponsors. The process is difficult but manageable and essential for efficient trial conduct. Close collaboration during trial conduct is a key component of any trial that includes real-time adaptive decision rules.

2.
Stat Med ; 40(24): 5199-5217, 2021 10 30.
Artigo em Inglês | MEDLINE | ID: mdl-34636054

RESUMO

A Bayesian phase I-II design is presented that optimizes the dose of a new agent within predefined prognostic subgroups. The design is motivated by a trial to evaluate targeted agents for treating metastatic clear cell renal carcinoma, where a prognostic risk score defined by clinical variables and biomarkers is well established. Two clinical outcomes are used for dose-finding, time-to-toxicity during a prespecified follow-up period, and efficacy characterized by ordinal disease status evaluated at the end of follow-up. A joint probability model is constructed for these outcomes as functions of dose and subgroup. The model performs adaptive clustering of adjacent subgroups having similar dose-outcome distributions to facilitate borrowing information across subgroups. To quantify toxicity-efficacy risk-benefit trade-offs that may differ between subgroups, the objective function is based on outcome utilities elicited separately for each subgroup. In the context of the renal cancer trial, a design is constructed and a simulation study is presented to evaluate the design's reliability, safety, and robustness, and to compare it to designs that either ignore subgroups or run a separate trial within each subgroup.


Assuntos
Projetos de Pesquisa , Teorema de Bayes , Ensaios Clínicos Fase I como Assunto , Ensaios Clínicos Fase II como Assunto , Simulação por Computador , Relação Dose-Resposta a Droga , Probabilidade , Prognóstico , Reprodutibilidade dos Testes
3.
Cancers (Basel) ; 13(11)2021 Jun 01.
Artigo em Inglês | MEDLINE | ID: mdl-34205968

RESUMO

We argue that well-informed patient-specific decision-making may be carried out as three consecutive tasks: (1) estimating key parameters of a statistical model, (2) using prognostic information to convert these parameters into clinically interpretable values, and (3) specifying joint utility functions to quantify risk-benefit trade-offs between clinical outcomes. Using the management of metastatic clear cell renal cell carcinoma as our motivating example, we explain the role of prognostic covariates that characterize between-patient heterogeneity in clinical outcomes. We show that explicitly specifying the joint utility of clinical outcomes provides a coherent basis for patient-specific decision-making.

4.
Bayesian Anal ; 16(1): 179-202, 2021 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-34267857

RESUMO

This paper proposes a Bayesian adaptive basket trial design to optimize the dose-schedule regimes of an experimental agent within disease subtypes, called "baskets", for phase I-II clinical trials based on late-onset efficacy and toxicity. To characterize the association among the baskets and regimes, a Bayesian hierarchical model is assumed that includes a heterogeneity parameter, adaptively updated during the trial, that quantifies information shared across baskets. To account for late-onset outcomes when doing sequential decision making, unobserved outcomes are treated as missing values and imputed by exploiting early biomarker and low-grade toxicity information. Elicited joint utilities of efficacy and toxicity are used for decision making. Patients are randomized adaptively to regimes while accounting for baskets, with randomization probabilities proportional to the posterior probability of achieving maximum utility. Simulations are presented to assess the design's robustness and ability to identify optimal dose-schedule regimes within disease subtypes, and to compare it to a simplified design that treats the subtypes independently.

5.
Front Immunol ; 12: 675679, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33995420

RESUMO

Background: COVID-19 Convalescent plasma (CCP) is safe and effective, particularly if given at an early stage of the disease. Our study aimed to identify an association between survival and specific antibodies found in CCP. Patients and Methods: Patients ≥18 years of age who were hospitalized with moderate to severe COVID-19 infection and received CCP at the MD Anderson Cancer Center between 4/30/2020 and 8/20/2020 were included in the study. We quantified the levels of anti-SARS-CoV-2 antibodies, as well as antibodies against antigens of other coronavirus strains, in the CCP units and compared antibody levels with patient outcomes. For each antibody, a Bayesian exponential survival time regression model including prognostic variables was fit, and the posterior probability of a beneficial effect (PBE) of higher antibody level on survival time was computed. Results: CCP was administered to 44 cancer patients. The median age was 60 years (range 37-84) and 19 (43%) were female. Twelve patients (27%) died of COVID-19-related complications. Higher levels of two non-SARS-CoV-2-specific antibodies, anti-HCoV-OC43 spike IgG and anti-HCoV-HKU1 spike IgG, had PBE = 1.00, and 4 SARS-CoV-2-specific antibodies had PBEs between 0.90 and 0.95. Other factors associated with better survival were shorter time to CCP administration, younger age, and female sex. Conclusions: Common cold coronavirus spike IgG antibodies anti-HCoV-OC43 and anti-HCoV-HKU1 may target a common domain for SARS-CoV-2 and other coronaviruses. They provide a promising therapeutic target for monoclonal antibody production.


Assuntos
Anticorpos Antivirais , Betacoronavirus/imunologia , COVID-19/terapia , Resfriado Comum/imunologia , Convalescença , Coronavirus Humano OC43/imunologia , SARS-CoV-2/imunologia , Glicoproteína da Espícula de Coronavírus/imunologia , Adulto , Idoso , Idoso de 80 Anos ou mais , Anticorpos Antivirais/administração & dosagem , Anticorpos Antivirais/imunologia , COVID-19/imunologia , COVID-19/mortalidade , Reações Cruzadas , Feminino , Humanos , Imunização Passiva , Masculino , Pessoa de Meia-Idade
6.
J Clin Oncol ; 39(24): 2710-2719, 2021 08 20.
Artigo em Inglês | MEDLINE | ID: mdl-33929874

RESUMO

PURPOSE: BK virus-associated hemorrhagic cystitis (BKV-HC) is a common complication of allogenic hematopoietic stem cell transplantation (AHSCT), particularly in recipients of alternative donor transplants, which are being performed in increasing numbers. BKV-HC typically results in painful hematuria, urinary obstruction, and renal dysfunction, without a definitive therapeutic option. METHODS: We performed a clinical trial (ClinicalTrials.gov identifier: NCT02479698) to assess the feasibility, safety, and efficacy of administering most closely HLA-matched third-party BKV-specific cytotoxic T lymphocytes (CTLs), generated from 26 healthy donors and banked for off-the-shelf use. The cells were infused into 59 patients who developed BKV-HC following AHSCT. Comprehensive clinical assessments and correlative studies were performed. RESULTS: Response to BKV-CTL infusion was rapid; the day 14 overall response rate was 67.7% (40 of 59 evaluable patients), which increased to 81.6% among evaluable patients at day 45 (40 of 49 evaluable patients). No patient lost a previously achieved response. There were no cases of de novo grade 3 or 4 graft-versus-host disease, graft failure, or infusion-related toxicities. BKV-CTLs were identified in patient blood samples up to 3 months postinfusion and their in vivo expansion predicted for clinical response. A matched-pair analysis revealed that, compared with standard of care, after accounting for prognostic covariate effects, treatment with BKV-CTLs resulted in higher probabilities of response at all follow-up timepoints as well as significantly lower transfusion requirement. CONCLUSION: Off-the-shelf BKV-CTLs are a safe and effective therapy for the management of patients with BKV-HC after AHSCT.


Assuntos
Cistite/tratamento farmacológico , Transtornos Hemorrágicos/tratamento farmacológico , Linfócitos T Citotóxicos/metabolismo , Alotransplante de Tecidos Compostos Vascularizados/efeitos adversos , Adolescente , Adulto , Idoso , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Estudos Prospectivos , Adulto Jovem
7.
medRxiv ; 2021 Mar 10.
Artigo em Inglês | MEDLINE | ID: mdl-33758890

RESUMO

Background: COVID-19 Convalescent plasma (CCP) is safe and effective, particularly if given at an early stage of the disease. Our study aimed to identify an association between survival and specific antibodies found in CCP. Patients and Methods: Patients ≥18 years of age who were hospitalized with moderate to severe COVID-19 infection and received CCP at the MD Anderson Cancer Center between 4/30/2020 and 8/20/2020 were included in the study. We quantified the levels of anti-SARS-CoV-2 antibodies, as well as antibodies against antigens of other coronavirus strains, in the CCP units and compared antibody levels with patient outcomes. For each antibody, a Bayesian exponential survival time regression model including prognostic variables was fit, and the posterior probability of a beneficial effect (PBE) of higher antibody level on survival time was computed. Results: CCP was administered to 44 cancer patients. The median age was 60 years (range 37-84) and 19 (43%) were female. Twelve patients (27%) died of COVID-19-related complications. Higher levels of two non-SARS-CoV-2-specific antibodies, anti-HCoV-OC43 spike IgG and anti-HCoV-HKU1 spike IgG, had PBE = 1.00, and 4 SARS-CoV-2-specific antibodies had PBEs between 0.90 and 0.95. Other factors associated with better survival were shorter time to CCP administration, younger age, and female sex. Conclusions: Common cold coronavirus spike IgG antibodies anti-HCoV-OC43 and anti-HCoV-HKU1 may target a common domain for SARS-CoV-2 and other coronaviruses. They provide a promising therapeutic target for monoclonal antibody production.

8.
Biometrics ; 2021 Jan 13.
Artigo em Inglês | MEDLINE | ID: mdl-33438761

RESUMO

Precision medicine relies on the idea that, for a particular targeted agent, only a subpopulation of patients is sensitive to it and thus may benefit from it therapeutically. In practice, it is often assumed based on preclinical data that a treatment-sensitive subpopulation is known, and moreover that the agent is substantively efficacious in that subpopulation. Due to important differences between preclinical settings and human biology, however, data from patients treated with a new targeted agent often show that one or both of these assumptions are false. This paper provides a Bayesian randomized group sequential enrichment design that compares an experimental treatment to a control based on survival time and uses early response as an ancillary outcome to assist with adaptive variable selection and enrichment. Initially, the design enrolls patients under broad eligibility criteria. At each interim decision, submodels for regression of response and survival time on a baseline covariate vector and treatment are fit; variable selection is used to identify a covariate subvector that characterizes treatment-sensitive patients and determines a personalized benefit index, and comparative superiority and futility decisions are made. Enrollment of each cohort is restricted to the most recent adaptively identified treatment-sensitive patients. Group sequential decision cutoffs are calibrated to control overall type I error and account for the adaptive enrollment restriction. The design provides a basis for precision medicine by identifying a treatment-sensitive subpopulation, if it exists, and determining whether the experimental treatment is superior to the control in that subpopulation. A simulation study shows that the proposed design reliably identifies a sensitive subpopulation, yields much higher generalized power compared to several existing enrichment designs and a conventional all-comers group sequential design, and is robust.

9.
Cancer ; 127(8): 1228-1237, 2021 04 15.
Artigo em Inglês | MEDLINE | ID: mdl-33306202

RESUMO

BACKGROUND: Risk of recurrence among patients with oropharyngeal cancer (OPC) who survive 5 years is low. The goal of this study was to assess long-term survival of patients with OPC alive without recurrence 5 years after diagnosis. METHODS: This study included newly diagnosed patients with OPC, who had been treated with radiation and were alive without recurrence 5 years after diagnosis. Overall survival (OS) probabilities beyond 5 years were estimated using the Kaplan-Meier method. Factors associated with OS were determined using Bayesian piecewise exponential survival regression. Standardized mortality ratios for all-cause death were estimated controlling for study year, age, and sex in the US general population. RESULTS: Among 1699 patients, the additional 2-year, 5-year, and 10-year OS probabilities were 94%, 83%, and 63%, respectively, and were lower than those in the general population. Patients who were older, were current or former smokers, had other than tonsil or base of tongue tumors, or had T4 tumors had a higher risk of death. Patients who had base of tongue tumors and had received intensity-modulated radiation therapy (IMRT) or lower-radiation doses had a lower risk of death. Standardized mortality ratios were higher among current and heavy smokers and lower among recipients of IMRT and lower radiation doses. CONCLUSIONS: In this large cohort, long-term survival among patients with OPC was good but lower than predicted for the general population. Patients treated with IMRT and those with less tobacco exposure had better outcomes.


Assuntos
Sobreviventes de Câncer , Neoplasias Orofaríngeas/mortalidade , Neoplasias Orofaríngeas/radioterapia , Fatores Etários , Idoso , Teorema de Bayes , Causas de Morte , Ex-Fumantes , Feminino , Humanos , Estimativa de Kaplan-Meier , Masculino , Pessoa de Meia-Idade , Recidiva Local de Neoplasia , Dosagem Radioterapêutica , Radioterapia de Intensidade Modulada , Estudos Retrospectivos , Fumantes , Fatores de Tempo , Neoplasias da Língua/mortalidade , Neoplasias da Língua/radioterapia
10.
Blood Adv ; 4(21): 5580-5588, 2020 11 10.
Artigo em Inglês | MEDLINE | ID: mdl-33170934

RESUMO

This study investigated the efficacy and safety of azacitidine maintenance in the posttransplant setting based on the encouraging phase 1/2 reports for azacitidine maintenance in patients with acute myeloid leukemia/myelodysplastic syndrome (AML/MDS). Between 2009 and 2017, a total of 187 patients aged 18 to 75 years were entered into a randomized controlled study of posttransplant azacitidine if they were in complete remission. Patients randomized to the treatment arm (n = 93) were scheduled to receive azacitidine, given as 32 mg/m2 per day subcutaneously for 5 days every 28 days for 12 cycles. The control arm (n = 94) had no intervention. Eighty-seven of the 93 patients started azacitidine maintenance. The median number of cycles received was 4; a total of 29 patients relapsed on study, and 23 patients withdrew from the study due to toxicity, patient's preference, or logistical reasons. Median relapse-free survival (RFS) was 2.07 years in the azacitidine group vs 1.28 years in the control group (P = .43). There was also no significant difference for overall survival, with a median of 2.52 years vs 2.56 years in the azacitidine and control groups (P = .85), respectively. Multivariate Cox regression analysis revealed no improvement in RFS or overall survival with the use of azacitidine as maintenance compared with the control group (hazard ratios of 0.73 [95% confidence interval, 0.49-1.1; P = .14] and 0.84 [95% confidence interval, 0.55-1.29; P = .43]) [corrected]. This randomized trial with azacitidine maintenance showed that a prospective trial in the posttransplant setting was feasible and safe but challenging. Although RFS was comparable between the 2 arms, we believe the strategy of maintenance therapy merits further study with a goal to reduce the risk of relapse in patients with AML/MDS. This trial was registered at www.clinicaltrials.gov as #NCT00887068.


Assuntos
Leucemia Mieloide Aguda , Síndromes Mielodisplásicas , Adolescente , Adulto , Idoso , Azacitidina/uso terapêutico , Humanos , Leucemia Mieloide Aguda/tratamento farmacológico , Pessoa de Meia-Idade , Síndromes Mielodisplásicas/tratamento farmacológico , Estudos Prospectivos , Indução de Remissão , Adulto Jovem
11.
Cancers (Basel) ; 12(11)2020 Nov 04.
Artigo em Inglês | MEDLINE | ID: mdl-33158080

RESUMO

This article introduces the adverse event (AE) burden score. The AE burden by treatment cycle is a weighted sum of all grades and AEs that the patient experienced in a cycle. The overall AE burden score is the total AE burden the patient experienced across all treatment cycles. AE data from two completed Alliance multi-center randomized double-blind placebo-controlled trials, with different AE profiles (NCCTG 97-24-51: 176 patients, and A091105: 83 patients), were utilized for illustration. Results of the AE burden score analyses corroborated the trials' primary results. In 97-24-51, the overall AE burden for patients on the treatment arm was 2.2 points higher than those on the placebo arm, with a higher AE burden for patients who went off treatment early due to AE. Similarly, in A091105, the overall AE burden was 1.6 points higher on the treatment arm. On the placebo arms, the AE burden in 97-24-51 remained constant over time; and increased in later cycles in A091105, likely attributable to the increase in disease morbidity. The AE burden score enables statistical comparisons analogous to other quantitative endpoints in clinical trials, and can readily accommodate different trial settings, diseases, and treatments, with diverse AE profiles.

12.
Radiother Oncol ; 152: 49-55, 2020 11.
Artigo em Inglês | MEDLINE | ID: mdl-32745668

RESUMO

BACKGROUND AND PURPOSE: Spine stereotactic radiosurgery (SSRS) offers high rates of local control in a critical anatomic area by delivering precise, ablative doses of radiation for treatment of spine metastases. However, the dose tolerance of the spinal cord (SC) after SSRS with relation to radiation myelopathy (RM) is not well-described. MATERIALS AND METHODS: We reviewed patients who underwent single fraction, de novo SSRS from 2012-2017 and received >12 Gy Dmax to the SC, defined using MRI-CT fusion without PRV expansion. The standard SC constraint was D0.01cc ≤ 12 Gy. Local control was estimated with the Kaplan-Meier method. Bayesian analysis was used to compute posterior probabilities for RM. RESULTS: A total of 146 SSRS treatments among 132 patients were included. The median SC Dmax was 12.6 Gy (range, 12.1-17.1 Gy). The SC Dmax was >12 and <13 Gy for 109 (75%) treatments, ≥13 and <14 Gy for 28 (19%) treatments, and ≥14 Gy for 9 (6%) treatments. The 1-year local control rate was 94%. With a median follow-up time of 42 months, there were zero (0) RM events observed. Assuming a prior 4.3% risk of RM, the true rate of RM for SC Dmax of ≤14 Gy was computed as <1% with 98% probability. CONCLUSION: In one of the largest series of patients treated with single fraction, de novo SSRS, there were no cases of RM observed with a median follow-up of 42 months. These data support safe relaxation of MRI-defined SC dose up to D0.01cc ≤ 12 Gy, which corresponds to <1% risk of RM.


Assuntos
Radiocirurgia , Doenças da Medula Espinal , Neoplasias da Coluna Vertebral , Teorema de Bayes , Humanos , Radiocirurgia/efeitos adversos , Medula Espinal , Doenças da Medula Espinal/etiologia , Neoplasias da Coluna Vertebral/radioterapia
13.
Contemp Clin Trials ; 97: 106099, 2020 10.
Artigo em Inglês | MEDLINE | ID: mdl-32822828

RESUMO

A semi-parametric stochastic ordering model (SPSO) is introduced to characterize functional relationships between dose level and the probabilities of binary Efficacy and Toxicity events. This model is used to implement a Bayesian adaptive phase I-II clinical trial using one of two different optimality criteria, either dose desirability defined as a function of the marginal Efficacy and Toxicity probabilities, or mean utility based on numerical scores of the four possible (Efficacy, Toxicity) events. A simulation study is conducted to compare designs using the SPSO model to the parametric EffTox model described in Thall and Cook, with each (model, optimality criterion) combination. Each of these four designs adaptively assigns patient cohorts to estimated optimal dose levels after restricting assignments to dose levels that are acceptably efficacious and safe. The simulation study shows that different design configurations may have superior performance depending on the assumed true dose-outcome scenario.


Assuntos
Projetos de Pesquisa , Teorema de Bayes , Ensaios Clínicos Fase I como Assunto , Ensaios Clínicos Fase II como Assunto , Simulação por Computador , Relação Dose-Resposta a Droga , Humanos , Medição de Risco
14.
Pharm Stat ; 19(6): 928-939, 2020 11.
Artigo em Inglês | MEDLINE | ID: mdl-32720462

RESUMO

When designing phase II clinical trials, it is important to construct interim monitoring rules that achieve a balance between reliable early stopping for futility or safety and maintaining a high true positive probability (TPP), which is the probability of not stopping if the new treatment is truly safe and effective. We define and compare several methods for specifying early stopping boundaries as functions of interim sample size, rather than as fixed cut-offs, using Bayesian posterior probabilities as decision criteria. We consider boundaries with constant, linear, or exponential shapes. For design optimization criteria, we use the TPP and mean number of patients enrolled in the trial. Simulations to evaluate and compare the designs' operating characteristics under a range of scenarios show that, while there is no uniformly optimal boundary, an appropriately calibrated exponential shape maintains high TPP while limiting the number of patients assigned to a treatment with an inferior response rate or an excessive toxicity rate.


Assuntos
Ensaios Clínicos Fase II como Assunto/estatística & dados numéricos , Término Precoce de Ensaios Clínicos/estatística & dados numéricos , Projetos de Pesquisa/estatística & dados numéricos , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , Teorema de Bayes , Linfoma de Burkitt/diagnóstico , Linfoma de Burkitt/tratamento farmacológico , Simulação por Computador , Interpretação Estatística de Dados , Humanos , Futilidade Médica , Modelos Estatísticos , Fatores de Tempo , Resultado do Tratamento
15.
Contemp Clin Trials ; 90: 105860, 2020 03.
Artigo em Inglês | MEDLINE | ID: mdl-31678411

RESUMO

Two illustrative applications are presented of Bayesian clinical trial designs that make adaptive subgroup-specific decisions based on elicited utilities of patient outcomes to quantify risk-benefit trade-offs. The first design is for a randomized trial to evaluate effects of nutritional prehabilitation on post-operative morbidity in esophageal cancer patients undergoing surgery. The second design is for a dose-finding trial of natural killer cells to treat advanced hematologic malignancies, with five time-to-event outcomes. Each design is based on a Bayesian hierarchical model that borrows strength between subgroups. Computer simulation is used to evaluate each design's properties, including comparison to a simpler design ignoring treatment-subgroup interactions. The simulations show that accounting prospectively for treatment-subgroup interactions yields designs with very desirable properties, is greatly superior to a simplified comparator design that ignores subgroups if treatment-subgroup interactions actually exist, and each design is robust to deviations from the assumed underlying model.


Assuntos
Teorema de Bayes , Ensaios Clínicos Fase I como Assunto/métodos , Ensaios Clínicos Fase II como Assunto/métodos , Projetos de Pesquisa , Biomarcadores , Simulação por Computador , Neoplasias Esofágicas/dietoterapia , Neoplasias Hematológicas/terapia , Humanos , Células Matadoras Naturais/metabolismo , Medicina de Precisão
16.
Biometrics ; 76(1): 304-315, 2020 03.
Artigo em Inglês | MEDLINE | ID: mdl-31273750

RESUMO

This paper proposes a two-stage phase I-II clinical trial design to optimize dose-schedule regimes of an experimental agent within ordered disease subgroups in terms of the toxicity-efficacy trade-off. The design is motivated by settings where prior biological information indicates it is certain that efficacy will improve with ordinal subgroup level. We formulate a flexible Bayesian hierarchical model to account for associations among subgroups and regimes, and to characterize ordered subgroup effects. Sequentially adaptive decision-making is complicated by the problem, arising from the motivating application, that efficacy is scored on day 90 and toxicity is evaluated within 30 days from the start of therapy, while the patient accrual rate is fast relative to these outcome evaluation intervals. To deal with this in a practical manner, we take a likelihood-based approach that treats unobserved toxicity and efficacy outcomes as missing values, and use elicited utilities that quantify the efficacy-toxicity trade-off as a decision criterion. Adaptive randomization is used to assign patients to regimes while accounting for subgroups, with randomization probabilities depending on the posterior predictive distributions of utilities. A simulation study is presented to evaluate the design's performance under a variety of scenarios, and to assess its sensitivity to the amount of missing data, the prior, and model misspecification.


Assuntos
Ensaios Clínicos Adaptados como Assunto/métodos , Ensaios Clínicos Adaptados como Assunto/estatística & dados numéricos , Biometria/métodos , Teorema de Bayes , Ensaios Clínicos Fase I como Assunto/métodos , Ensaios Clínicos Fase I como Assunto/estatística & dados numéricos , Ensaios Clínicos Fase II como Assunto/métodos , Ensaios Clínicos Fase II como Assunto/estatística & dados numéricos , Simulação por Computador , Tomada de Decisões Assistida por Computador , Relação Dose-Resposta a Droga , Esquema de Medicação , Humanos , Modelos Estatísticos , Avaliação de Resultados em Cuidados de Saúde/métodos , Avaliação de Resultados em Cuidados de Saúde/estatística & dados numéricos , Tamanho da Amostra
17.
Ann Appl Stat ; 13(1): 221-247, 2019 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-31681453

RESUMO

We propose a Bayesian semiparametric joint regression model for a recurrent event process and survival time. Assuming independent latent subject frailties, we define marginal models for the recurrent event process intensity and survival distribution as functions of the subject's frailty and baseline covariates. A robust Bayesian model, called Joint-DP, is obtained by assuming a Dirichlet process for the frailty distribution. We present a simulation study that compares posterior estimates under the Joint-DP model to a Bayesian joint model with lognormal frailties, a frequentist joint model, and marginal models for either the recurrent event process or survival time. The simulations show that the Joint-DP model does a good job of correcting for treatment assignment bias, and has favorable estimation reliability and accuracy compared with the alternative models. The Joint-DP model is applied to analyze an observational dataset from esophageal cancer patients treated with chemo-radiation, including the times of recurrent effusions of fluid to the heart or lungs, survival time, prognostic covariates, and radiation therapy modality.

18.
J R Stat Soc Ser C Appl Stat ; 68(3): 809-828, 2019 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-31467455

RESUMO

Allogeneic stem cell transplantation (allo-SCT) is now part of standard of care for acute leukemia (AL). To reduce toxicity of the pre-transplant conditioning regimen, intravenous busulfan is usually used as a preparative regimen for AL patients undergoing allo-SCT. Systemic busulfan exposure, characterized by the area under the plasma concentration versus time curve (AUC), is strongly associated with clinical outcome. An AUC that is too high is associated with severe toxicities, while an AUC that is too low carries increased risks of disease recurrence and failure to engraft. Consequently, an optimal AUC interval needs to be determined for therapeutic use. To address the possibility that busulfan pharmacokinetics and pharmacodynamics vary significantly with patient characteristics, we propose a tailored approach to determine optimal covariate-specific AUC intervals. To estimate these personalized AUC intervals, we apply a flexible Bayesian nonparametric regression model based on a dependent Dirichlet process and Gaussian process, DDP-GP. Our analyses of a dataset of 151 patients identified optimal therapeutic intervals for AUC that varied substantively with age and whether the patient was in complete remission or had active disease at transplant. Extensive simulations to evaluate the DDP-GP model in similar settings showed that its performance compares favorably to alternative methods. We provide an R package, DDPGPSurv, that implements the DDP-GP model for a broad range of survival regression analyses.

20.
J R Stat Soc Ser C Appl Stat ; 68(2): 461-474, 2019 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-31105345

RESUMO

A sequentially adaptive Bayesian design is presented for a clinical trial of cord blood derived natural killer cells to treat severe hematologic malignancies. Given six prognostic subgroups defined by disease type and severity, the goal is to optimize cell dose in each subgroup. The trial has five co-primary outcomes, the times to severe toxicity, cytokine release syndrome, disease progression or response, and death. The design assumes a multivariate Weibull regression model, with marginals depending on dose, subgroup, and patient frailties that induce association among the event times. Utilities of all possible combinations of the nonfatal outcomes over the first 100 days following cell infusion are elicited, with posterior mean utility used as a criterion to optimize dose. For each subgroup, the design stops accrual to doses having an unacceptably high death rate, and at the end of the trial selects the optimal safe dose. A simulation study is presented to validate the design's safety, ability to identify optimal doses, and robustness, and to compare it to a simplified design that ignores patient heterogeneity.

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