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1.
Stat Med ; 41(11): 1918-1931, 2022 May 20.
Artigo em Inglês | MEDLINE | ID: mdl-35098585

RESUMO

In the era of immunotherapies and targeted therapies, the focus of early phase clinical trials has shifted from finding the maximum tolerated dose to identifying the optimal biological dose (OBD), which maximizes the toxicity-efficacy trade-off. One major impediment to using adaptive designs to find OBD is that efficacy or/and toxicity are often late-onset, hampering the designs' real-time decision rules for treating new patients. To address this issue, we propose the model-assisted TITE-BOIN12 design to find OBD with late-onset toxicity and efficacy. As an extension of the BOIN12 design, the TITE-BOIN12 design also uses utility to quantify the toxicity-efficacy trade-off. We consider two approaches, Bayesian data augmentation and an approximated likelihood method, to enable real-time decision making when some patients' toxicity and efficacy outcomes are pending. Extensive simulations show that, compared to some existing designs, TITE-BOIN12 significantly shortens the trial duration while having comparable or higher accuracy to identify OBD and a lower risk of overdosing patients. To facilitate the use of the TITE-BOIN12 design, we develop a user-friendly software freely available at http://www.trialdesign.org.


Assuntos
Ensaios Clínicos Fase I como Assunto , Ensaios Clínicos Fase II como Assunto , Projetos de Pesquisa , Teorema de Bayes , Simulação por Computador , Relação Dose-Resposta a Droga , Humanos , Imunoterapia/efeitos adversos , Dose Máxima Tolerável
2.
Stat Methods Med Res ; 30(10): 2269-2287, 2021 10.
Artigo em Inglês | MEDLINE | ID: mdl-34468238

RESUMO

The area under the receiver operating characteristic curve is a widely used measure for evaluating the performance of a diagnostic test. Common approaches for inference on area under the receiver operating characteristic curve are usually based upon approximation. For example, the normal approximation based inference tends to suffer from the problem of low accuracy for small sample size. Frequentist empirical likelihood based approaches for area under the receiver operating characteristic curve estimation may perform better, but are usually conducted through approximation in order to reduce the computational burden, thus the inference is not exact. By contrast, we proposed an exact inferential procedure by adapting the empirical likelihood into a Bayesian framework and draw inference from the posterior samples of the area under the receiver operating characteristic curve obtained via a Gibbs sampler. The full conditional distributions within the Gibbs sampler only involve empirical likelihoods with linear constraints, which greatly simplify the computation. To further enhance the applicability and flexibility of the Bayesian empirical likelihood, we extend our method to the estimation of partial area under the receiver operating characteristic curve, comparison of multiple tests, and the doubly robust estimation of area under the receiver operating characteristic curve in the presence of missing test results. Simulation studies confirm the desirable performance of the proposed methods, and a real application is presented to illustrate its usefulness.


Assuntos
Testes Diagnósticos de Rotina , Área Sob a Curva , Teorema de Bayes , Simulação por Computador , Funções Verossimilhança , Curva ROC
3.
Biostatistics ; 2021 Jul 23.
Artigo em Inglês | MEDLINE | ID: mdl-34296266

RESUMO

Identification of the optimal dose presents a major challenge in drug development with molecularly targeted agents, immunotherapy, as well as chimeric antigen receptor T-cell treatments. By casting dose finding as a Bayesian model selection problem, we propose an adaptive design by simultaneously incorporating the toxicity and efficacy outcomes to select the optimal biological dose (OBD) in phase I/II clinical trials. Without imposing any parametric assumption or shape constraint on the underlying dose-response curves, we specify curve-free models for both the toxicity and efficacy endpoints to determine the OBD. By integrating the observed data across all dose levels, the proposed design is coherent in dose assignment and thus greatly enhances efficiency and accuracy in pinning down the right dose. Not only does our design possess a completely new yet flexible dose-finding framework, but it also has satisfactory and robust performance as demonstrated by extensive simulation studies. In addition, we show that our design enjoys desirable coherence properties, while most of existing phase I/II designs do not. We further extend the design to accommodate late-onset outcomes which are common in immunotherapy. The proposed design is exemplified with a phase I/II clinical trial in chronic lymphocytic leukemia.

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.
Int J Radiat Oncol Biol Phys ; 111(4): 907-916, 2021 11 15.
Artigo em Inglês | MEDLINE | ID: mdl-34302893

RESUMO

PURPOSE: Cardiotoxicities induced by cancer therapy can negatively affect quality of life and survival. We investigated whether high-sensitivity cardiac troponin T (hs-cTnT) levels could serve as biomarker for early detection of cardiac adverse events (CAEs) after chemoradiation therapy (CRT) for non-small cell lung cancer (NSCLC). METHODS AND MATERIALS: This study included 225 patients who received concurrent platinum and taxane-doublet chemotherapy with thoracic radiation therapy to a total dose of 60 to 74 Gy for NSCLC. All patients were evaluated for CAEs; 190 patients also had serial hs-cTnT measurements. RESULTS: Grade ≥3 CAEs occurred in 24 patients (11%) at a median interval of 9 months after CRT. Pretreatment hs-cTnT levels were higher in men, in patients aged ≥64 years, and in patients with pre-existing heart disease or poor performance status (P < .05). hs-cTnT levels increased at 4 weeks during CRT (P < .05) and decreased after completion of CRT but did not return to pretreatment levels (P = .002). The change (Δ) in hs-cTnT levels during CRT correlated with mean heart dose (P = .0004), the heart volumes receiving 5 to 55 Gy (P < .05), and tumor location (P = .006). Risks of severe CAEs and mortality were significantly increased if the pretreatment hs-cTnT was >10 ng/L or the Δ during CRT was ≥5 ng/L. CONCLUSIONS: Elevation of hs-cTnT during CRT was radiation heart dose-dependent, and high hs-cTnT levels during the course of CRT were associated with CAEs and mortality. Routine monitoring of hs-cTnT could identify patients who are at high risk of CRT-induced CAEs early to guide modifications of cancer therapy and possible interventions to mitigate cardiotoxicity.


Assuntos
Carcinoma Pulmonar de Células não Pequenas , Neoplasias Pulmonares , Biomarcadores , Carcinoma Pulmonar de Células não Pequenas/terapia , Cardiotoxicidade , Humanos , Neoplasias Pulmonares/terapia , Masculino , Prognóstico , Estudos Prospectivos , Qualidade de Vida , Troponina T
6.
J Hematol Oncol ; 14(1): 89, 2021 06 09.
Artigo em Inglês | MEDLINE | ID: mdl-34108026

RESUMO

BACKGROUND: Accurate appraisal of burden of adolescents and young adults (AYAs) cancers is crucial to informing resource allocation and policy making. We report on the latest estimates of burden of AYA cancers in 204 countries and territories between 1990 and 2019 in association with socio-demographic index (SDI). PATIENTS AND METHODS: Estimates from the Global Burden of Disease study 2019 were used to analyse incidence, mortality, and disability-adjusted life years (DALYs) due to AYA cancers at global, regional, and national levels by sex. Association between AYA cancer burden and SDI were investigated. Burdens of AYA cancers were contextualized in comparison with childhood and older adult cancers. All estimates are reported as counts and age-standardized rates per 100,000 person-years. RESULTS: In 2019, there were 1.2 million incident cases, 0.4 million deaths, and 23.5 million DALYs due to AYA cancers globally. The highest age-standardized incidence rate occurred in Western Europe (75.3 [Females] and 67.4 [Males] per 100,000 person-years). Age-standardized death (23.2 [Females] and 13.9 [Males] per 100,000 person-years) and DALY (1328.3 [Females] and 1059.2 [Males] per 100,000 person-years) rates were highest in Oceania. Increasing SDI was associated with a higher age-standardized incidence rate. An inverted U-shaped association was identified between SDI and death and DALY rates. AYA cancers collectively is the second leading cause of non-communicable diseases-related deaths globally in 2019. DALYs of AYA cancers ranked the second globally and the first in low and low-middle SDI locations when compared with that of childhood and older adult cancers. CONCLUSION: The global burden of AYA cancers is substantial and disproportionally affect populations in limited-resource settings. Capacity building for AYA cancers is essential in promoting equity and population health worldwide.


Assuntos
Carga Global da Doença , Neoplasias/epidemiologia , Adolescente , Adulto , Feminino , Saúde Global , Humanos , Incidência , Masculino , Anos de Vida Ajustados por Qualidade de Vida , Adulto Jovem
7.
Pharm Stat ; 20(6): 1183-1199, 2021 11.
Artigo em Inglês | MEDLINE | ID: mdl-34008317

RESUMO

Bayesian sequential monitoring is widely used in adaptive phase II studies where the objective is to examine whether an experimental drug is efficacious. Common approaches for Bayesian sequential monitoring are based on posterior or predictive probabilities and Bayesian hypothesis testing procedures using Bayes factors. In the first part of the paper, we briefly show the connections between test-based (TB) and posterior probability-based (PB) sequential monitoring approaches. Next, we extensively investigate the choice of local and nonlocal priors for the TB monitoring procedure. We describe the pros and cons of different priors in terms of operating characteristics. We also develop a user-friendly Shiny application to implement the TB design.


Assuntos
Projetos de Pesquisa , Teorema de Bayes , Humanos , Probabilidade
8.
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
9.
Stat Med ; 40(11): 2626-2649, 2021 05 20.
Artigo em Inglês | MEDLINE | ID: mdl-33650708

RESUMO

Unlike chemotherapy, the maximum tolerated dose (MTD) of molecularly targeted agents and immunotherapy may not pose significant clinical benefit over the lower doses. By simultaneously considering both toxicity and efficacy endpoints, phase I/II trials can identify a more clinically meaningful dose for subsequent phase II trials than traditional toxicity-based phase I trials in terms of risk-benefit tradeoff. To strengthen and simplify the current practice of phase I/II trials, we propose a utility-based toxicity probability interval (uTPI) design for finding the optimal biological dose, based on a numerical utility that provides a clinically meaningful, one-dimensional summary representation of the patient's bivariate toxicity and efficacy outcome. The uTPI design does not rely on any parametric specification of the dose-response relationship, and it directly models the dose desirability through a quasi binomial likelihood. Toxicity probability intervals are used to screen out overly toxic dose levels, and then the dose escalation/de-escalation decisions are made adaptively by comparing the posterior desirability distributions of the adjacent levels of the current dose. The uTPI design is flexible in accommodating various dose desirability formulations, while only requiring minimum design parameters. It has a clear decision structure such that a dose-assignment decision table can be calculated before the trial starts and can be used throughout the trial, which simplifies the practical implementation of the design. Extensive simulation studies demonstrate that the proposed uTPI design yields desirable as well as robust performance under various scenarios.


Assuntos
Antineoplásicos , Teorema de Bayes , Ensaios Clínicos Fase I como Assunto , Ensaios Clínicos Fase II como Assunto , Simulação por Computador , Relação Dose-Resposta a Droga , Humanos , Dose Máxima Tolerável , Modelos Estatísticos , Probabilidade , Projetos de Pesquisa
10.
JCO Clin Cancer Inform ; 5: 91-101, 2021 01.
Artigo em Inglês | MEDLINE | ID: mdl-33439726

RESUMO

PURPOSE: Using novel Bayesian adaptive designs has great potential to improve the efficiency of early-phase clinical trials. A major barrier for clinical researchers to adopt novel designs is the lack of easy-to-use software. Our purpose is to develop a user-friendly software platform to implement novel clinical trial designs that address various challenges in early-phase dose-finding trials. METHODS: We used R Shiny to develop a web-based software platform to facilitate the use of recent novel adaptive designs. RESULTS: We developed a web-based software suite, called Bayesian optimal interval (BOIN) suite, which includes R Shiny applications to handle various clinical settings, including single-agent phase I trials with and without prior information, trials with late-onset toxicity, trials to find the optimal biological dose based on risk-benefit trade-off, and drug combination trials to find a single maximum tolerated dose (MTD) or the MTD contour. The applications are built using the same software architecture to ensure the best and a uniform user experience, and they are developed using a proven software development standard operating procedure to ensure accuracy, robustness, and reproducibility. The suite is freely available with internet access and a web browser without the need of installing any other software. CONCLUSION: The BOIN suite allows clinical researchers to design various types of early-phase clinical trials under a unified framework. This work is extremely important because it not only advances the clinical research and drug development by facilitating the use of novel trial designs with optimal performance but also enhances collaborations between biostatisticians and clinicians by disseminating novel statistical methodology to broader scientific communities through user-friendly software. The BOIN suite establishes a KISS principle: keep it simple, but smart.


Assuntos
Modelos Estatísticos , Neoplasias , Software , Teorema de Bayes , Ensaios Clínicos como Assunto , Simulação por Computador , Relação Dose-Resposta a Droga , Humanos , Reprodutibilidade dos Testes
11.
Contemp Clin Trials ; 100: 106216, 2021 01.
Artigo em Inglês | MEDLINE | ID: mdl-33246098

RESUMO

Clinical trial participants are often heterogeneous, which is a fundamental problem in the rapidly developing field of precision medicine. Participants heterogeneity causes considerable difficulty in the current phase III trial designs. Adaptive enrichment designs provide a flexible and intuitive solution. At the interim analysis, we enrich the subgroup of trial participants who have a higher likelihood to benefit from the new treatment. However, it is critical to control the level of the test size and maintain adequate power after enrichment of certain subgroup of participants. We develop two adaptive enrichment strategies with sample size re-estimation and verify their feasibility and practicability through extensive simulations and sensitivity analyses. The simulation studies show that the proposed methods can control the overall type I error rate and exhibit competitive improvement in terms of statistical power and expected sample size. The proposed designs are exemplified with a real trial application.


Assuntos
Projetos de Pesquisa , Ensaios Clínicos como Assunto , Simulação por Computador , Humanos , Tamanho da Amostra
12.
Artigo em Inglês | MEDLINE | ID: mdl-33283133

RESUMO

PURPOSE: For immunotherapy, such as checkpoint inhibitors and chimeric antigen receptor T-cell therapy, where the efficacy does not necessarily increase with the dose, the maximum tolerated dose may not be the optimal dose for treating patients. For these novel therapies, the objective of dose-finding trials is to identify the optimal biologic dose (OBD) that optimizes patients' risk-benefit trade-off. METHODS: We propose a simple and flexible Bayesian optimal interval phase I/II (BOIN12) trial design to find the OBD that optimizes the risk-benefit trade-off. The BOIN12 design makes the decision of dose escalation and de-escalation by simultaneously taking account of efficacy and toxicity and adaptively allocates patients to the dose that optimizes the toxicity-efficacy trade-off. We performed simulation studies to evaluate the performance of the BOIN12 design. RESULTS: Compared with existing phase I/II dose-finding designs, the BOIN12 design is simpler to implement, has higher accuracy to identify the OBD, and allocates more patients to the OBD. One of the most appealing features of the BOIN12 design is that its adaptation rule can be pretabulated and included in the protocol. During the trial conduct, clinicians can simply look up the decision table to allocate patients to a dose without complicated computation. CONCLUSION: The BOIN12 design is simple to implement and yields desirable operating characteristics. It overcomes the computational and implementation complexity that plagues existing Bayesian phase I/II dose-finding designs and provides a useful design to optimize the dose of immunotherapy and targeted therapy. User-friendly software is freely available to facilitate the application of the BOIN12 design.

13.
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
15.
Contemp Clin Trials ; 92: 105972, 2020 05.
Artigo em Inglês | MEDLINE | ID: mdl-32151751

RESUMO

The Keyboard design is a novel model-assisted dose-finding method to find the maximum tolerated dose (MTD) for single-agent trials. The Keyboard design is easy to implement and has superior performance in comparison to more complicated model-assisted designs. In this article, we extend the Keyboard design to dual-agent dose-finding trials. The proposed Keyboard combination trial design maintains the simplicity of the original single-agent Keyboard design, and its dose escalation and deescalation rules can be pre-tabulated before conducting the trial. We show that the Keyboard combination design has desirable theoretical properties, including the optimality of its decision rules, coherence in dose transition, and convergence to the target dose. Extensive simulations are conducted to evaluate the performance of the proposed Keyboard combination design using a novel, random two-dimensional dose-toxicity scenario generating algorithm. The simulation results confirm the desirable and competitive operating characteristics of the Keyboard design. An R Shiny application is available at www.trialdesign.org to implement the Keyboard combination design.


Assuntos
Ensaios Clínicos Fase I como Assunto/métodos , Combinação de Medicamentos , Dose Máxima Tolerável , Projetos de Pesquisa , Algoritmos , Teorema de Bayes , Simulação por Computador , Relação Dose-Resposta a Droga , Humanos
16.
J Natl Cancer Inst ; 112(1): 38-45, 2020 01 01.
Artigo em Inglês | MEDLINE | ID: mdl-30924863

RESUMO

BACKGROUND: Immunotherapies have revolutionized cancer treatment. Unlike chemotherapies, immune agents often take longer to show benefit, and the complex and unique mechanism of action of these agents renders the use of multiple endpoints more appropriate in some trials. These new features of immunotherapy make conventional phase II trial designs, which assume a single binary endpoint that is quickly ascertainable, inefficient and dysfunctional. METHODS: We propose a flexible and efficient time-to-event Bayesian optimal phase II (TOP) design. The TOP design is efficient in that it allows real-time "go/no-go" interim decision making in the presence of late-onset responses by using all available data and maximizes statistical power for detecting effective treatments. TOP is flexible in the number of interim looks and capable of handling simple and complicated endpoints under a unified framework. We conduct simulation studies to evaluate the operating characteristics of the TOP design. RESULTS: In the considered trial settings, compared to some existing Bayesian designs, the TOP design shortens the trial duration by 4-10 months and improves the power to detect effective treatment up to 90%, with well-controlled type I errors. CONCLUSIONS: The TOP design is transparent and easy to implement, as its decision rules can be tabulated and included in the protocol prior to the conduct of the trial. The TOP design provides a flexible, efficient, and easy-to-implement method to accelerate and improve the development of immunotherapies.


Assuntos
Teorema de Bayes , Ensaios Clínicos Fase II como Assunto/métodos , Ensaios Clínicos Fase II como Assunto/normas , Imunoterapia , Oncologia , Projetos de Pesquisa , Software , Algoritmos , Simulação por Computador , Determinação de Ponto Final , Humanos , Imunoterapia/métodos , Imunoterapia/normas , Oncologia/métodos , Oncologia/normas , Prognóstico , Tamanho da Amostra , Resultado do Tratamento
17.
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
18.
Biostatistics ; 21(4): 807-824, 2020 10 01.
Artigo em Inglês | MEDLINE | ID: mdl-30984972

RESUMO

Two useful strategies to speed up drug development are to increase the patient accrual rate and use novel adaptive designs. Unfortunately, these two strategies often conflict when the evaluation of the outcome cannot keep pace with the patient accrual rate and thus the interim data cannot be observed in time to make adaptive decisions. A similar logistic difficulty arises when the outcome is late-onset. Based on a novel formulation and approximation of the likelihood of the observed data, we propose a general methodology for model-assisted designs to handle toxicity data that are pending due to fast accrual or late-onset toxicity and facilitate seamless decision making in phase I dose-finding trials. The proposed time-to-event model-assisted designs consider each dose separately and the dose-escalation/de-escalation rules can be tabulated before the trial begins, which greatly simplifies trial conduct in practice compared to that under existing methods. We show that the proposed designs have desirable finite and large-sample properties and yield performance that is comparable to that of more complicated model-based designs. We provide user-friendly software for implementing the designs.


Assuntos
Projetos de Pesquisa , Software , Teorema de Bayes , Ensaios Clínicos Fase I como Assunto , Simulação por Computador , Relação Dose-Resposta a Droga , Humanos , Dose Máxima Tolerável
19.
J Biopharm Stat ; 29(4): 648-662, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31258039

RESUMO

In phase I dose-finding trials, model-assisted designs are a novel class of designs that combine the simplicity of algorithm-based methods with the superior performance of model-based methods. Examples of model-assisted designs include the modified toxicity probability (mTPI), Bayesian optimal interval (BOIN) and keyboard designs. To achieve simplicity, these model-assisted methods model only "local" data observed at the current dose, typically using a binomial model, to guide dose assignments. This potentially causes efficiency loss, however, by ignoring the data observed in other doses. To investigate this issue, we propose a conditional approach that utilizes the data from both current and adjacent (i.e., next higher or lower) doses to make the dose-assignment decisions. Specifically, we propose the conditional optimal interval (COIN) design, as the conditional approach extension of the BOIN design. We investigate the theoretical properties of the COIN design and conduct extensive numerical studies to examine its performance in comparison with existing model-assisted designs. We also present the conditional approach to the keyboard design. We observe that the conditional approach improves patient allocation, but yields similar maximum-tolerated dose (MTD) identification accuracy as the model-assisted designs, suggesting only minor efficiency loss using local data under the model-assisted designs.


Assuntos
Ensaios Clínicos Fase I como Assunto , Projetos de Pesquisa , Teorema de Bayes , Simulação por Computador , Humanos , Dose Máxima Tolerável
20.
Front Oncol ; 9: 404, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31214489

RESUMO

Background: Although lung cancer incidence and mortality have been declining since the 1990s, the extent to which such progress has been made is unequal across population segments. Updated epidemiologic data on trends and patterns of disparities are lacking. Methods: Data on lung cancer cases and deaths during 1974 to 2015 were extracted from the Surveillance, Epidemiology, and End Results program. Age-standardized lung cancer incidence and mortality and their annual percent changes were calculated by histologic types, demographic variables, and tumor characteristics. Results: Lung cancer incidence decreased since 1990 (1990 to 2007: annual percent change, -0.9 [95% CI, -1.0%, -0.8%]; 2007 to 2015: -2.6 [-2.9%, -2.2%]). Among adults aged between 20 and 39 years, a higher incidence was observed among females during 1995 to 2011, after which a faster decline in female lung cancer incidence (males: -2.5% [-2.8%, -2.2%]; females: -3.1% [-4.7%, -1.5%]) resulted in a lower incidence among females. The white population had a higher incidence than the Black population for small cell carcinoma since 1987. Black females were the only group whose adenocarcinoma incidence plateaued since 2012 (-5.0% [-13.0%, 3.7%]). A higher incidence for squamous cell carcinoma was observed among Black males and females than among white males and females during 1974 to 2015. After circa 2005, octogenarians and older patients constituted the group with the highest lung cancer incidence. Incidence for localized and AJCC/TNM stage I lung cancer among octogenarians and older patients plateaued since 2009, while mortality continued to rise (localized: 1.4% [0.6%, 2.1%]; stage I: 6.7% [4.5%, 9.0%]). Conclusions: Lung cancer disparities prevail across population segments. Our findings inform effective approaches to eliminate lung cancer disparities by targeting at-risk populations.

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