Browse
Submit Data
Databases
API
Help

Dataset Information

26 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Clinical Predictors of Early Trial Discontinuation for Patients Participating in Phase I Clinical Trials in Oncology.

ABSTRACT: Despite stringent eligibility criteria for trial participation, early discontinuation often occurs in phase I trials. To better identify patients unlikely to benefit from phase I trials, we investigated predictors for early trial discontinuation. Data from 415 patients with solid tumors who participated in 66 trials were pooled for the current analysis. Early trial discontinuation was defined as (i) trial discontinuation within 28 days after start of treatment or (ii) discontinuation before administration of the first dosage in eligible patients. Multilevel logistic regression analyses were conducted to identify predictors for early trial discontinuation. Eighty-two participants (20%) demonstrated early trial discontinuation. Baseline sodium level below the lower limit of normal (OR = 2.95, 95%CI = 1.27-6.84), elevated alkaline phosphatase level > 2.5 times the upper limit of normal (OR = 2.72, 95%CI = 1.49-4.99), performance score ≥ 1 (OR = 2.07, 95%CI = 1.03-4.19) and opioid use (OR = 1.82, 95%CI = 1.07-3.08) were independent predictors for early trial discontinuation. Almost 50% of the patients with hyponatremia and all four patients in whom all four predictors were present together discontinued the trial early. Hyponatremia, elevated alkaline phosphatase level, performance score ≥ 1 and opioid use were identified as significant predictors for early trial discontinuation. Hyponatremia was the strongest predictor and deserves consideration for inclusion in eligibility criteria for future trials.

SUBMITTER: Douma JAJ

PROVIDER: S-EPMC8151105 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Predictors of early treatment discontinuation in patients enrolled on Phase I oncology trials.

Project description:Patients who do not complete one cycle of therapy on Phase I trials for reasons other than dose limiting toxicity (DLT) are considered inevaluable for toxicity and must be replaced.Individual records from patients enrolled to NCI-sponsored Phase I trials activated between 2000 and 2010 were used. Early discontinuation was defined as the failure to begin cycle 2 for reasons other than a DLT during cycle 1. A multinomial logistic regression with a 3-level nominal outcome (early discontinuation, DLT during cycle 1, and continuation to cycl1e 2) was used with continuation to cycle 2 serving as the reference category. The final model was used to create two risk scores. An independent external cohort was used to validate these models.Data from 3079 patients on 127 Phase I trials were analyzed. ECOG performance status (1, ? 2, two-sided P = .0315 and P = .0007), creatinine clearance (<60 ml/min, P = .0455), alkaline phosphatase (>2.5xULN, P = .0026), AST (>ULN, P = .0076), hemoglobin (<10 g/dL, P < .0001), albumin (<3.5 g/dL, P < .0001), and platelets (<400x109/L, P = .0732) were predictors of early discontinuation. The c-index of the final model was 0.63.Knowledge of risk factors for early treatment discontinuation in conjunction with clinical judgment can help guide Phase I patient selection.

| S-EPMC4662493 | biostudies-literature

COVID-19 vaccine guidance for patients with cancer participating in oncology clinical trials.

Project description:Emerging efficacy data have led to the emergency use authorization or approval of COVID-19 vaccines in several countries worldwide. Most trials of COVID-19 vaccines excluded patients with active malignancies, and thus data on the safety, tolerability and efficacy of the vaccines in patients with cancer are currently limited. Given the risk posed by the COVID-19 pandemic, decisions regarding the use of vaccines against COVID-19 in patients participating in trials of investigational anticancer therapies need to be addressed promptly. Patients should not have to choose between enrolling on oncology clinical trials and receiving a COVID-19 vaccine. Clinical trial sponsors, investigators and treating physicians need operational guidance on COVID-19 vaccination for patients with cancer who are currently enrolled or might seek to enrol in clinical trials. Considering the high morbidity and mortality from COVID-19 in patients with cancer, the benefits of vaccination are likely to far outweigh the risks of vaccine-related adverse events. Herein, we provide operational COVID-19 vaccine guidance for patients participating in oncology clinical trials. In our perspective, continued quality oncological care requires that patients with cancer, including those involved in trials, be prioritized for COVID-19 vaccination, which should not affect trial eligibility.

| S-EPMC7957448 | biostudies-literature

Precision Oncology for Cancer Immunotherapies in Early-Phase Clinical Trials.

Project description:The clinical development of cancer drugs is rapidly moving from empirical "one drug fits all" or development-by-tumor-type approaches towards more personalized treatment models. A deeper understanding of cancer and the immune system, novel technologies, and powerful analytics have fueled an increase in precision oncology approaches integrating the molecular profiles of the tumor with the clinical profile of the patient. While this approach has been successful for targeted therapies, the complex mode of action of immunotherapies will likely require integration of clinical profiling with more comprehensive profiling of the tumor, of the tumor microenvironment, and of the immune system of the patient. Integration of precision oncology into clinical research for immunotherapies is viewed as a means to better select patients in the early clinical phase of drug development to (1) maximize the benefit-to-risk ratio for the patient, (2) generate early proof of concept and proof of relevance for the investigational drug, and (3) inform on how to best combine or sequence the therapeutic with other drugs. Here we discuss the upsides and challenges of incorporating precision immuno-oncology into early-phase clinical trials.

| S-EPMC6875515 | biostudies-literature

Design considerations for early-phase clinical trials of immune-oncology agents.

Project description:BACKGROUND:With numerous and fast approvals of different agents including immune checkpoint inhibitors, monoclonal antibodies, or chimeric antigen receptor (CAR) T-cell therapy, immunotherapy is now an established form of cancer treatment. These agents have demonstrated impressive clinical activity across many tumor types, but also revealed different toxicity profiles and mechanisms of action. The classic assumptions imposed by cytotoxic agents may no longer be applicable, requiring new strategies for dose selection and trial design. DESCRIPTION:This main goal of this article is to summarize and highlight main challenges of early-phase study design of immunotherapies from a statistical perspective. We compared the underlying toxicity and efficacy assumptions of cytotoxic versus immune-oncology agents, proposed novel endpoints to be included in the dose-selection process, and reviewed design considerations to be considered for early-phase trials. When available, references to software and/or web-based applications were also provided to ease the implementation. Throughout the paper, concrete examples from completed (pembrolizumab, nivolumab) or ongoing trials were used to motivate the main ideas including recommendation of alternative designs. CONCLUSION:Further advances in the effectiveness of cancer immunotherapies will require new approaches that include redefining the optimal dose to be carried forward in later phases, incorporating additional endpoints in the dose selection process (PK, PD, immune-based biomarkers), developing personalized biomarker profiles, or testing drug combination therapies to improve efficacy and reduce toxicity.

| S-EPMC6103998 | biostudies-literature

Pre-clinical animal models are poor predictors of human toxicities in phase 1 oncology clinical trials.

Project description:BackgroundOur objective was to determine the correlation between preclinical toxicity found in animal models (mouse, rat, dog and monkey) and clinical toxicity reported in patients participating in Phase 1 oncology clinical trials.MethodsWe obtained from two major early-Phase clinical trial centres, preclinical toxicities from investigational brochures and clinical toxicities from published Phase 1 trials for 108 drugs, including small molecules, biologics and conjugates. Toxicities were categorised according to Common Terminology Criteria for Adverse Events version 4.0. Human toxicities were also categorised based on their reported clinical grade (severity). Positive predictive values (PPV) and negative predictive values (NPV) were calculated to determine the probability that clinical studies would/would not show a particular toxicity category given that it was seen in preclinical toxicology analysis. Statistical analyses also included kappa statistics, and Matthews (MCC) and Spearman correlation coefficients.ResultsOverall, animal toxicity did not show strong correlation with human toxicity, with a median PPV of 0.65 and NPV of 0.50. Similar results were obtained based on kappa statistics and MCC.ConclusionsThere is an urgent need to assess more novel approaches to the type and conduct of preclinical toxicity studies in an effort to provide better predictive value for human investigation.

| S-EPMC7652903 | biostudies-literature

Unequal allotment of patients in phase III oncology clinical trials.

Project description:Patient enrollment in cancer clinical trials has traditionally been limited to an equal distribution between cases and controls, however recently some clinical trials have utilized an unequal distribution between the case and control arms. Trends and proportion of phase 3 cancer clinical trials that have an unequal allocation between the years 2010 and 2019 were studied from data extracted from clinicaltrials.gov. 323 trials with two arms and 35 trials with 3 arms were identified as randomized control trials with the primary purpose of a cancer-related treatment that provided allocation data. Amongst the trials with two arms, 238 trials had equal allocation and 85 trials had unequal allocation. Therefore, cancer clinical trials with unequal allocation represent about one in four 2-arm phase 3 trials. Amongst the eligible trials with three arms, 26 trials had equal allocation and 9 trials had unequal allocation. There was no significant difference in the annual proportion of trials with unequal allocation from 2010 to 2019. The categories of cancer which had the highest number of unequally allotted two-arm clinical trials were: gastrointestinal, breast, and genitourinary malignancies. This shift may represent a new trend in clinical trial design to help enhance closer monitoring of adverse events despite higher costs and lower statistical power attached to this method.

| S-EPMC8332855 | biostudies-literature

Insurance Clearance for Early-Phase Oncology Clinical Trials Following the Affordable Care Act.

Project description:Purpose: The Affordable Care Act (ACA) required that private insurance plans allow clinical trial participation and cover standard-of-care costs, but the impact of this provision has not been well-characterized. We assessed rates of insurance clearance for trial participation within our large early-phase clinical trials program, before and after implementation of the requirement.Experimental Design: We analyzed the departmental database for the Clinical Center for Targeted Therapy (CCTT) at MD Anderson Cancer Center (Houston, TX). Among patients referred for sponsored trials, we described rates of insurance clearance and prolonged time to clearance (at least 14 days) from July 2012 to June 2013 (baseline), July 2013-December 2013 (following CCTT staffing changes in July 2103), and January 2014-June 2015 (following implementation of the ACA). We used multivariable logistic regression models to compare rates across these time periods.Results: We identified 2,404 referrals for insurance clearance. Among privately insured patients, insurance clearance rates were higher for those referred from January 2014 to June 2015 than for those referred from July 2012 to June 2013 (OR, 4.72; 95% CI, 2.96-7.51). There was no association between referral period and clearance rates for Medicare/Medicaid patients (P = 0.25). Referral from January 2014 to June 2015 was associated with lower rates of prolonged clearance among both privately insured (OR 0.57; 95% CI, 0.38-0.86) and Medicare/Medicaid patients (OR 0.39; 95% CI, 0.19-0.83).Conclusions: Within our large early-phase clinical trials program, insurance clearance rates among privately insured patients improved following implementation of the ACA's requirement for coverage of standard-of-care costs. Clin Cancer Res; 23(15); 4155-62. ©2017 AACR.

| S-EPMC5902668 | biostudies-literature

Randomised Phase 1 clinical trials in oncology.

Project description:The aims of Phase 1 trials in oncology have broadened considerably from simply demonstrating that the agent/regimen of interest is well tolerated in a relatively heterogeneous patient population to addressing multiple objectives under the heading of early-phase trials and, if possible, obtaining reliable evidence regarding clinical activity to lead to drug approvals via the Accelerated Approval approach or Breakthrough Therapy designation in cases where the tumours are rare, prognosis is poor or where there might be an unmet therapeutic need. Constructing a Phase 1 design that can address multiple objectives within the context of a single trial is not simple. Randomisation can play an important role, but carrying out such randomisation according to the principles of equipoise is a significant challenge in the Phase 1 setting. If the emerging data are not sufficient to definitively address the aims early on, then a proper design can reduce biases, enhance interpretability, and maximise information so that the Phase 1 data can be more compelling. This article outlines objectives and design considerations that need to be adhered to in order to respect ethical and scientific principles required for research in human subjects in early phase clinical trials.

| S-EPMC8476627 | biostudies-literature

Age and race distribution in patients in phase III oncology clinical trials.

Project description:Background: Geriatric patients and minority patients are often under-represented in cancer clinical trials. The presence of multiple comorbidities makes geriatric patients ineligible for most clinical trials. Racial diversity may vary by geographical location and socio-economically backward areas may have a very different racial mix. The increase in cancer incidence in geriatric patients' raises the question of applicability of the results is such clinical trials. This study also explores the representation of different races in phase 3 clinical trials conducted in the past 10 years. Methods: Data about Phase III trials was extracted from the clinical trials.gov for 3 common solid organs and 3 hematological malignancies [breast, colon, lung, diffuse large B-cell lymphoma (DLBCL), acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL)]. The time period studied was for the past 10 years and included only adult patients (≥18 years). The age and race distribution of the patient population in these trials were extracted and analyzed. Results: Geriatric patients and minorities are under-represented in all phase III cancer clinical trials. The range of the proportion of geriatric patients varied from 10% to 40%. African American and Asian patients are under-represented in all phase III cancer clinical trials. Conclusions: The results of phase III clinical trials that are currently conducted on non-geriatric and Caucasian patient population may not meaningfully be applicable to geriatric patients and minorities. This study highlights the disparity of age and race for patients enrolled in clinical trials as against the patients seen in the real world.

| S-EPMC7540092 | biostudies-literature

Discrepancies in endpoints between clinical trial protocols and clinical trial registration in randomized trials in oncology.

Project description:BACKGROUND:Clinical trials are an essential part of evidence-based medicine. Hence, to ensure transparency and accountability in these clinical trials, policies for registration have been framed with emphasis on mandatory submission of trial elements, specifically outcome measures. As these efforts evolve further, we sought to evaluate the current status of endpoint reporting in clinical trial registries. METHODS:We reviewed 71 oncology related randomized controlled trials published in three high impact journals. We compared primary (PEP) and non-primary endpoints (NPEP) between the clinical trial protocols of these trials and their corresponding registration in one of the 14 primary global clinical trial registries. A discrepancy was defined as the non-reporting or absence of an endpoint in either the protocol or registry. The primary endpoint was the rate of discrepancy between secondary endpoints in clinical trial protocols and clinical trial registries. RESULTS:Of the 71 clinical trials, a discrepancy in PEP was found in only 4 trials (6%). Secondary endpoint (SEP) differences were found in 45 (63%) trials. Among these 45 trials, 36 (80%) had SEPs that were planned in the protocol but not reported in the registry and 19 (42%) had SEPs with endpoints in the registry that were not found in the protocol. The total number of SEPs that were absent from the corresponding registry and protocol were 84 and 29, respectively. Of these endpoints, 48 (57%) and 9 (31%) were included in the published report of these trials. CONCLUSION:Although recent regulations and enhanced procedures have improved the number and quality of clinical trial registrations, inconsistencies regarding endpoint reporting still exist. Though further guidelines for the registration of clinical trials will help, greater efforts to provide a correct, easily accessible, and complete representation of planned endpoints are needed.

| S-EPMC6292048 | biostudies-other

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data