scholarly journals Importance and role of independent data monitoring committees (IDMCs) in oncology clinical trials

BMJ Open ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. e047294
Author(s):  
P Schöffski
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Adverse Events ◽  
Stopping Rules ◽  
Data Monitoring ◽  
Independent Data ◽  
Oncology Clinical Trials ◽  
Life Threatening ◽  
Study Participants

The role and use of independent data monitoring committees (IDMCs) has evolved over the past decades. The Food and Drug Administration and European Medicines Agency have issued guidelines on the role and functioning of such committees. In general, data monitoring committees are recommended for large, often randomised clinical trials involving life-threatening diseases, studies performed in vulnerable populations or where the experimental intervention can potentially harm the trial participant. Such committees play an important role in trials evaluating treatments with the potential to prolong life or reduce the risk of major adverse health outcomes.Typically, oncology clinical trials fall within these recommendations, as they are often large, randomised, multicentric protocols aiming at improving survival outcomes by exploring the use of study treatments that may be associated with a significant risk of serious, even life-threatening adverse events. IDMCs are required for National Cancer Institute phase III randomised trials, European Organisation for Research and Treatment of Cancer phase II/III trials with formal interim analyses, early-stopping rules or adaptive studies. The primary role of an IDMC of ensuring the safety of study participants and maintaining clinical trial integrity is particularly important in oncology trials, due to the nature of the disease, the potential for treatment toxicity and for instilling confidence that the clinical trial data are reliable. A clear understanding by IDMC members of the natural course of the disease, treatment landscape, importance and relevance of certain adverse events in trial participants, clinical trial methodology in general and stopping rules for oncology trials in particular, is crucial for the functioning of an IDMC.It is recommended that IDMC members should be experienced trialists, have a track record of strong clinical, statistical and/or methodological expertise and the required level of independence, as they play a highly important role in the protection of study participants, and in commercially and strategically important go/no decisions. Ideally, IDMC members should have relevant experience or have some training, mentorship or guidelines.

A tool for assessing adverse events in phase I/II oncology clinical trials

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 6518-6518
Author(s):  
M. Coombes ◽  
S. Mukherjee ◽  
B. Kowaleski ◽  
M. Levine ◽  
J. Cosby ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Adverse Events ◽  
Phase I ◽  
Clinical Reasoning ◽  
Rating Scale ◽  
Assessment Tool ◽  
Causality Assessment ◽  
Information Resources ◽  
Oncology Clinical Trials

6518 Background: RECIST and NCI's Common Terminology Criteria are accepted systems that have standardized the reporting of oncology clinical trial outcomes. A standard system for attributing causality to Serious Adverse Events (SAEs) is lacking which can impact drug development and patient safety. The objectives of this study were to: 1) understand the clinical reasoning behind causality assessment during phase I/II oncology clinical trials; and, 2) use this information to develop a causality assessment tool for oncology. Methods: In-depth interviews were conducted with oncologists and trial coordinators at 6 Canadian academic cancer centres. Five main conceptual categories were explored: clinical reasoning; information resources; tools; challenges and concerns; and education. Interviews were recorded and transcribed verbatim. Individual interview content analysis was followed by thematic analysis across the interview set. A new causality assessment tool was developed based upon the qualitative findings and an analysis of existing generic tools. Results: Thirty-two interviews were conducted between May and August 2006 (65% participation). Half of participants were female, 66% were oncologists and 42% had more than 10 years of clinical trial experience. Data showed that participants use a common strategy to assess causality: they gather information, eliminate alternative explanations, and consider the study drug as the cause of the SAE. Over half cited the quality of information resources as a major factor contributing to uncertainty when assessing causality. Participants expressed the need for a standardized approach to causality assessment in oncology clinical trials. The tool developed in this study guides users to consider 5 statements related to potential alternative etiologies and 4 related to other factors that support a drug-SAE connection. The user is asked for their overall impression using a continuous probability rating scale. Conclusions: Attributing causality to SAEs is complex and uncertain. Clinicians describe using a logical system of reasoning, but have encountered barriers which must be addressed. We have developed and are validating a new tool to assist cancer clinicians in providing higher quality safety data about new cancer drugs early in development. [Table: see text]

Dedicated clinical trial tissue tracking database to improve turn-around time at high-volume center.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 1543-1543
Author(s):  
Peter Blankenship ◽  
David DeLaRosa ◽  
Marc Burris ◽  
Steven Cusson ◽  
Kayla Hendricks ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Tissue Sample ◽  
High Volume ◽  
Trial Participation ◽  
Fresh Tissue ◽  
Oncology Clinical Trials ◽  
The Status ◽  
Unique Source

1543 Background: Tissue requirements in oncology clinical trials are increasingly complex due to prescreening protocols for patient selection and serial biopsies to understand molecular-level treatment effects. Novel solutions for tissue processing are necessary for timely tissue procurement. Based on these needs, we developed a Tissue Tracker (TT), a comprehensive database for study-related tissue tasks at our high-volume clinical trial center. Methods: In this Microsoft Access database, patients are assigned an ID within the TT that is associated with their name, medical record number, and study that follows their request to external users: pathology departments, clinical trial coordinators and data team members. To complete tasks in the TT, relevant information is required to update the status. Due to the high number of archival tissue requests from unique pathology labs, the TT has a “Follow-Up Dashboard” that organizes information needed to conduct follow-up on all archival samples with the status “Requested”. This results in an autogenerated email and pdf report sent to necessary teams. The TT also includes a kit inventory system and a real-time read only version formatted for interdepartmental communication, metric reporting, and other data-driven efforts. The primary outcome in this study was to evaluate our average turnaround time (ATAT: average time from request to shipment) for archival and fresh tissue samples before and after TT development. Results: Before implementing the TT, between March 2016 and March 2018, we processed 2676 archival requests from 235 unique source labs resulting in 2040 shipments with an ATAT of 19.29 days. We also processed 1099 fresh biopsies resulting in 944 shipments with an ATAT of 7.72 days. After TT implementation, between April 2018 and April 2020, we processed 2664 archival requests from 204 unique source labs resulting in 2506 shipments (+28.0%) with an ATAT of 14.78 days (-23.4%). During that same period, we processed 1795 fresh biopsies (+63.3%) resulting in 2006 shipments (+112.5%) with an ATAT of 6.85 days (-11.3%). Conclusions: Oncology clinical trials continue to evolve toward more extensive tissue requirements for prescreening and scientific exploration of on-treatment molecular profiling. Timely results are required to optimize patient trial participation. During the intervention period, our tissue sample volume and shipments increased, but the development and implementation of an automated tracking system allowed improvement in ATAT of both archival and fresh tissue. This automation not only improves end-user expectations and experiences for patients and trial sponsors but this allows our team to adapt to the increasing interest in tissue exploration.

scholarly journals Copy Number Signatures Predict Chromothripsis and Poor Clinical Outcome in Newly Diagnosed Multiple Myeloma Patients

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 52-53
Author(s):  
Kylee H Maclachlan ◽  
Binbin Zheng-Lin ◽  
Venkata Yellapantula ◽  
Andriy Derkach ◽  
Even H Rustad ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Clinical Trials ◽  
Research Funding ◽  
De Novo ◽  
Data Monitoring ◽  
Signature Analysis ◽  
Independent Data ◽  
Genetics Research ◽  
Manual Curation ◽  
Low Coverage

Chromothripsis is emerging as a strong and independent prognostic factor in multiple myeloma (MM), predicting shorter progression-free (PFS) and overall survival (Rustad BioRxiv 2019). Reliable detection requires whole genome sequencing (WGS), with 24% prevalence in 752 newly diagnosed multiple myeloma (NDMM) from CoMMpass (NCT01454297, Rustad BioRxiv 2019) compared with 1.3% by array-based techniques (Magrangeas Blood 2011). In MM, chromothripsis presents differently to solid cancers. Although the biological impact is similar across malignancies, in MM the structural complexity of chromothriptic events is typically lower. In addition, chromothripsis can occur early in MM development and remain stable over time (Maura Nat Comm 2019). Computational algorithms for chromothripsis detection (e.g. ShatterSeek; Cortes-Ciriano Nat Gen 2018) were developed in solid cancers and are accurate in that setting. Running ShatterSeek on 752 NDMM patients with low coverage WGS from CoMMpass, we observed a high specificity for chromothripsis (98.3%) but poor sensitivity (30.2%). ShatterSeek detected chromothripsis in 64/752 samples (8.5%), with 85% confirmed on manual curation; however, missed 114 cases located by manual curation. This indicates that MM-specific computational methods are required. We hypothesized that a signature analysis approach using copy number variation (CNV) may provide an accurate estimation of chromothripsis. We adapted CNV signature analysis, developed in ovarian cancer (Macintyre Nat Gen 2018), to now detect MM-specific CNV and structural features. The analysis utilizes 6 fundamental CN features: i) absolute CN of segments, ii) difference in CN in adjacent segments, iii) breakpoints per 10 Mb, iv) breakpoints per chromosome arm, v) lengths of oscillating CN segment chains, and vi) the size of segments. The optimal number of categories in each CNV feature was established using a mixed effect model (mclust R package). Using CoMMpass low-coverage WGS, de novo extraction using the hierarchical dirichlet process defined 5 signatures, 2 of which (CNV-SIG 4 and CNV-SIG 5) contain features associated with chromothripsis: longer lengths of oscillating CN states, higher numbers of breakpoints / chromosome arm, and higher total numbers of small segments of CN change. Next, we demonstrate that CNV signatures are highly predictive of chromothripsis (average area-under-the-curve /AUC = 0.9, based on 10-fold cross validation). Chromothripsis-associated CNV signatures are correlated with biallelic TP53 inactivation (p= 0.01) and gain1q21 (p<0.001) and show negative association with t(11;14) (p<0.001). Chromothriptic signatures were associated with shorter PFS, with multivariate analysis after correction for ISS, age, biallelic TP53 inactivation, t(4;14) and gain1q21 producing a hazard ratio of 2.9 (95% CI 1.07-7.7, p = 0.036). A validation set of 29 NDMM WGS confirmed the ability of CNV signatures to predict chromothripsis (AUC 0.87). As WGS is currently too expensive and computationally intensive to employ in routine practice, we investigated if CNV signatures can predict chromothripsis without using WGS. First, we performed de novo signature extraction using whole exome data from 865 CoMMpass samples. CNV signatures extracted without reference to WGS produced an AUC = 0.81 for predicting chromothripsis (in those with WGS to confirm; n =752), and the chromothriptic-signatures confirmed the association with a shorter PFS (HR=7.2, 95%CI 1.32-39.4, p = 0.022). Second, we applied CNV signature analysis to NDMM having either the myTYPE targeted sequencing panel (n= 113; Yellapantula, Blood Can J 2019) or a single nucleotide polymorphism (SNP) array (n= 217). CNV signature assessment by each technology was predictive of clinical outcome, likely due to the detection of chromothripsis. As with WGS, multivariate analysis confirmed CNV signatures to be independently prognostic (myTYPE; p = 0.003, SNP; p = 0.004). Overall, we demonstrate that CNV signature analysis in NDMM provides a highly accurate prediction of chromothripsis. CNV signature assessment remains reliable by multiple surrogate measures, without requiring WGS. Chromothripsis-associated CNV signatures are an independent and adverse prognostic factor, potentially allowing refinement of standard prognostic scores for NDMM patients and providing a more accurate risk stratification for clinical trials. Disclosures Hultcrantz: Amgen: Research Funding; Daiichi Sankyo: Research Funding; GSK: Research Funding; Intellisphere LLC: Consultancy. Dogan:Takeda: Consultancy; National Cancer Institute: Research Funding; Roche: Consultancy, Research Funding; Seattle Genetics: Consultancy; AbbVie: Consultancy; EUSA Pharma: Consultancy; Physicians Education Resource: Consultancy; Corvus Pharmaceuticals: Consultancy. Morgan:Bristol-Myers Squibb: Consultancy, Honoraria; Janssen: Research Funding; Karyopharm: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Roche: Consultancy, Honoraria; GSK: Consultancy, Honoraria. Landgren:Cellectis: Consultancy, Honoraria; Takeda: Other: Independent Data Monitoring Committees for clinical trials, Research Funding; BMS: Consultancy, Honoraria; Adaptive: Consultancy, Honoraria; Takeda: Other: Independent Data Monitoring Committees for clinical trials, Research Funding; Glenmark: Consultancy, Honoraria, Research Funding; Seattle Genetics: Research Funding; Binding Site: Consultancy, Honoraria; Karyopharma: Research Funding; Merck: Other; BMS: Consultancy, Honoraria; Karyopharma: Research Funding; Merck: Other; Pfizer: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Seattle Genetics: Research Funding; Juno: Consultancy, Honoraria; Juno: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Other: Independent Data Monitoring Committees for clinical trials, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Other: Independent Data Monitoring Committees for clinical trials, Research Funding; Pfizer: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding; Cellectis: Consultancy, Honoraria; Glenmark: Consultancy, Honoraria, Research Funding; Binding Site: Consultancy, Honoraria.

Safety and efficacy outcomes with nivolumab plus ipilimumab in patients with advanced renal cell carcinoma and low Karnofsky performance status: Results from the CheckMate 920 trial.

2021 ◽  
Vol 39 (6_suppl) ◽  
pp. 315-315
Author(s):  
Thomas E. Hutson ◽  
Bradley Curtis Carthon ◽  
Jeffrey Yorio ◽  
Sunil Babu ◽  
Heidi Ann McKean ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Renal Cell Carcinoma ◽  
Clinical Trials ◽  
Adverse Events ◽  
Clear Cell ◽  
Karnofsky Performance Status ◽  
Performance Status ◽  
Objective Response ◽  
Safety And Efficacy ◽  
Grade 3

315 Background: Combination therapy with nivolumab + ipilimumab (NIVO+IPI) has demonstrated long-term efficacy and tolerability for patients (pts) with previously untreated advanced renal cell carcinoma (aRCC). Most pivotal clinical trials in pts with aRCC have excluded pts with low Karnofsky performance status (KPS; < 70%). CheckMate 920 is a multi-arm, phase IIIb/IV, open-label clinical trial of NIVO+IPI treatment in pts enrolled in a community practice setting with aRCC and a high unmet medical need. We present safety and efficacy results for the cohort of pts with aRCC of any histology and KPS 50%–60% from CheckMate 920 (NCT02982954). Methods: Pts with previously untreated advanced/metastatic RCC and KPS 50%–60% received NIVO 3 mg/kg + IPI 1 mg/kg Q3W × 4 doses followed by 480 mg NIVO Q4W for ≤ 2 years or until disease progression/unacceptable toxicity. The primary endpoint was incidence of grade ≥ 3 immune-mediated adverse events (imAEs) within 100 days of last dose of study drug. Key secondary endpoints included progression-free survival (PFS) and objective response rate (ORR) by RECIST v1.1 (both per investigator). Exploratory endpoints included overall survival (OS). Results: Of 25 treated pts with KPS 50%–60%, 76% were men; median age was 67 years (range, 34–81). IMDC risk was favorable in 0%, intermediate in 32%, and poor in 68% of pts; 84% had clear cell and 16% had non-clear cell RCC histology. With a minimum follow-up of 25 months, median duration of therapy (95% CI) was 2.3 months (2.1–7.7) for NIVO and 2.1 months (2.1–2.1) for IPI. The median number of doses (range) received was 4 (1–27) for NIVO and 4 (1–4) for IPI; 76% of pts received ≥ 4 NIVO doses and 68% received all 4 IPI doses. The only grade 3–4 imAEs by category were hepatitis (4.0%) and adrenal insufficiency (4.0%). No grade 5 imAEs occurred. Overall, 4 (16%) pts discontinued due to any-grade adverse events (n = 1 each for elevated AST, malignant neoplasm progression, back pain, and acetabulum fracture). Of 18 evaluable pts, ORR was 33.3% (95% CI, 13.3–59.0); no pts had a complete response and 6 had partial response. Median time to objective response was 4.5 months (range, 2.5–24.7). Median duration of objective response was 20.6 months (range, 0.03+–24.2+). Median PFS was 4.6 months (95% CI, 2.5–14.8). Median OS was 15.6 months (95% CI, 5.3–25.1). Conclusions: NIVO+IPI demonstrated an acceptable safety profile and promising antitumor activity in pts with previously untreated aRCC and KPS 50%–60%. The combination was tolerated at a dose intensity similar to that observed in clinical trials conducted in pts with higher KPS (≥ 70%). These data support the value of NIVO+IPI in pts who may not be considered ideal candidates for this therapy and consequently may have limited treatment options. Clinical trial information: NCT02982954 .

Diarrhea in Placebo Arms of Cancer Studies

2021 ◽  
Vol 1 (5) ◽  
pp. 379-385
Author(s):  
BIRTE J. WOLFF ◽  
JOHANNES E. WOLFF
Keyword(s):  
Clinical Trials ◽  
Literature Review ◽  
Adverse Events ◽  
Healthy Volunteers ◽  
Cancer Prevention ◽  
Cancer Patients ◽  
Systematic Literature Review ◽  
Oncology Clinical Trials ◽  
Prevention Studies ◽  
Cancer Studies

Background/Aim: Diarrhea is among the most common adverse events in early oncology clinical trials, and drug causality may be difficult to determine. Materials and Methods: This is a systematic literature review of placebo arms of randomized cancer trials. Results: Anemia was reported in 95 of 127 placebo monotherapy cohorts. Publications involving healthy volunteers and cancer prevention studies reported lower frequencies than those with cancer patients. The average reported frequency of diarrhea grade 1 or higher among studies in cancer patients was 15%. The maximal reported frequencies for grades 1, 2, 3, 4, 5 were 56, 24, 6, 2, and 0%, respectively. Conclusion: When higher diarrhea frequencies than those are observed in treatment arms of clinical trials, then drug causality is likely.

A novel, hybrid, single- and multi-site clinical trial design for CLN3 disease, an ultra-rare lysosomal storage disorder

2019 ◽  
Vol 16 (5) ◽  
pp. 555-560 ◽  
Author(s):  
Heather R Adams ◽  
Sara Defendorf ◽  
Amy Vierhile ◽  
Jonathan W Mink ◽  
Frederick J Marshall ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Rare Diseases ◽  
Trial Design ◽  
Neurodegenerative Disorder ◽  
Clinical Trial Design ◽  
Trial Participation ◽  
Local Participation ◽  
Cln3 Disease ◽  
Study Participants

Background Travel burden often substantially limits the ability of individuals to participate in clinical trials. Wide geographic dispersion of individuals with rare diseases poses an additional key challenge in the conduct of clinical trials for rare diseases. Novel technologies and methods can improve access to research by connecting participants in their homes and local communities to a distant research site. For clinical trials, however, understanding of factors important for transition from traditional multi-center trial models to local participation models is limited. We sought to test a novel, hybrid, single- and multi-site clinical trial design in the context of a trial for Juvenile Neuronal Ceroid Lipofuscinosis (CLN3 disease), a very rare pediatric neurodegenerative disorder. Methods We created a “hub and spoke” model for implementing a 22-week crossover clinical trial of mycophenolate compared with placebo, with two 8-week study arms. A single central site, the “hub,” conducted screening, consent, drug dispensing, and tolerability and efficacy assessments. Each participant identified a clinician to serve as a collaborating “spoke” site to perform local safety monitoring. Study participants traveled to the hub at the beginning and end of each study arm, and to their individual spoke site in the intervening weeks. Results A total of 18 spoke sites were established for 19 enrolled study participants. One potential participant was unable to identify a collaborating local site and was thus unable to participate. Study start-up required a median 6.7 months (interquartile range = 4.6–9.2 months). Only 33.3% (n = 6 of 18) of spoke site investigators had prior clinical trial experience, thus close collaboration with respect to study startup, training, and oversight was an important requirement. All but one participant completed all study visits; no study visits were missed due to travel requirements. Conclusions This study represents a step toward local trial participation for patients with rare diseases. Even in the context of close oversight, local participation models may be best suited for studies of compounds with well-understood side-effect profiles, for those with straightforward modes of administration, or for studies requiring extended follow-up periods.

Improving attribution of adverse events in oncology clinical trials

2019 ◽  
Vol 76 ◽  
pp. 33-40 ◽  
Author(s):  
Goldy C. George ◽  
Pedro C. Barata ◽  
Alicyn Campbell ◽  
Alice Chen ◽  
Jorge E. Cortes ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Adverse Events ◽  
Oncology Clinical Trials
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