Clintrial Refer- a Mobile App To Connect Patients With Local Clinical Trials

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 5600-5600
Author(s):  
Judith Trotman ◽  
Xavier Badoux ◽  
Admir Huseincehajic ◽  
Michele Gambrill ◽  
Anais LeGall ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Clinical Research ◽  
Data Entry ◽  
Smart Phone ◽  
Mobile App ◽  
Research Network ◽  
Trial Participation ◽  
Time Data ◽  
App Development

Abstract Background Readily accessible, smart-phone applications (Apps) have the potential to revolutionise and improve the delivery of patient care. Significant challenges associated with recruiting patients to haematology clinical trials include the rarity of diseases, complexity of trials, limited site locations, and maintaining knowledge of current trials in the context of rapid therapeutic developments. The Haematology Clinical Research Network, of New South Wales and the Australian Capital Territory (NSW/ACT) aimed to develop an App to facilitate clinician and patient access to current information on local clinical trials and improve trial participation by increasing referrals. Methods Key objectives were to develop an App that was free to download, simple to use and effective. Only publically listed data was to be included. Endpoints were rates of App usage, and cross-site and internal clinical trial referrals. Through liaison between the end-users (clinicians, trial managers and patients), and the contracted software developer, App specifications were refined through successive iterations. With the key search filters of Disease, Location, Sponsor and Study Status, the App has an easy to navigate listing of currently recruiting haematology trials. Useful features include: listing of inclusion and exclusion criteria; direct links to ClinTrials.gov; a lay summary; and direct contacts from the mobile device to participating study sites. Real-time data entry into the database app manager ensures currency of trial information. Results ClinTrial Refer went live in May 2013, on both iOS and Android platforms. As at 10th August, ClinTrial Refer has 654 users, over 4358 sessions and 13924 screen views.91% of current users are repeat users. Despite its local application the App has been accessed in 46 countries. Among the target audience in NSW 290 repeat users returned for an average 11 sessions each indicating a high user acceptance. It is being endorsed on the websites of Australian blood cancer consumer groups. A survey has confirmed that since its launch, through having readily accessible data on their smart-phones, ClinTrial Refer has increased clinician awareness of the NSW trial portfolio. In just twelve weeks it has resulted in the cross-referral of an additional 30+ patients for clinical trials, representing a >300% increase over previous referral patterns. This improvement in trials knowledge management has also increased within-site recruitment; however it is harder to quantify the exact short-term impact of ClinTrial Refer within hospitals. The App has already been duplicated for other Australian state-wide haematology networks and the Adolescent & Young Adult Research Network, NSW. Conclusion ClinTrial Refer is an innovative but simple, readily accessible mobile Application. Its widespread adoption across 18 Haematology Clinical Research sites in NSW Australia is facilitating increased patient recruitment to trials. Only recently available on iTunes and Google Play, it has attracted national and international attention as a template for any clinical trial network portfolio. Disclosures: Trotman: Celgene: Grant for App development Other. Huseincehajic:Celgene: Grant for App development Other.

Increasing Cross-Referral and Recruitment to Clinical Trials: A New Approach

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 636-636 ◽  
Author(s):  
Roslyn Ristuccia ◽  
Xavier C Badoux ◽  
Melinda Gibson ◽  
Admir Huseincehajic ◽  
Judith Trotman
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Clinical Research ◽  
Conflicts Of Interest ◽  
Smart Phone ◽  
Basic Structure ◽  
Smartphone Application ◽  
Research Network ◽  
Research Staff ◽  
Mutational Status

Abstract Background/Aims The Haematology Clinical Research Network of New South Wales & the Australian Capital Territory (HCRN NSW/ACT) comprises public hospital clinical trial unit managers committed to collaboration in the clinical research endeavour. In June 2013 we launched the ClinTrial Refer Application (App) on iTunes and Google play. This smart-phone and iPAD/Tablet tool provided clinicians, research staff and patients with instant knowledge of currently recruiting local haematology trials. It was associated with an immediate increase in inter-hospital cross referrals of patients to trials. Following this, the HCRN aimed to sustain and measure this increased referral and trials recruitment and to create a not-for-profit 'template App' that could be transferrable to other clinical trial portfolios. Methods Patient cross-referral patterns, recruitment and staffing data were obtained from each of the 18 contributing hospitals in the HCRN from June 2013 to June 2015 and compared with prior to June 2013. Google analytics for the App were downloaded. We worked with research staff of other cancer networks to create modified versions of the App, establishing search functions unique to each network's geography and/or tumour stream. Newly derived Apps had to conform to the specifications of ClinTrial Refer, namely being publically available and free to download, simple to use and hosting only publically listed data of currently recruiting trials. Results Within the HCRN there has been a sustained increase in cross referrals for clinical trials (median 1/month (range 0-6) to 9/month (0-18)) (Figure 1) and a state-wide >50% increase in recruitment from 300 to 460 from 2012 to 2014 and a 20% increase in unit staffing from 2013 to 2014. Google analytics usage metrics identify 3362 App users, over 24,703 sessions lasting an average 56 seconds. 19,907 of these sessions are in NSW where 91% of users are repeat users. Ten other state and national haematology or other tumour stream ClinTrial Refer Apps have been derived from the original App, from Sept 2013 to July 2015 (Figure 2). While maintaining the basic structure of an easy-to-navigate listing of currently recruiting trials, each new App has been re-designed to ensure relevance for the needs of each network. This ranged from a simple re-configuration of the logo, splash screen and recruiting locations for other Australian haematology Apps, to providing mutational status options for melanoma trials or age criteria for paediatric and adolescent- young adult Networks. The back-end database of listed trials, selection criteria and recruiting sites can be rapidly easily updated by local trial unit managers ensuring currency of trial information (est. 30 minutes/month in total). The "early adopters" within other cancer research networks have reported a similar upswing in trials recruitment and Google analytics for these newer Apps are similarly impressive. Recognising ClinTrial Refer as an effective tool for patients to identify recruiting trials close to home, cancer consumer groups have posted the Apps on their websites. Conclusions An instantly accessible, simple smartphone Application has provided better knowledge management of local clinical trials across the spectrum of rare haematologic malignancies. A tool to facilitate collaboration in clinical research, it has significantly enhanced cross-referral and recruitment rates, increasing patient access to emerging therapies and supporting the viability of haematology clinical trial units across Australia. ClinTrial Refer has been rapidly adapted to suit the trials portfolios of other clinical trial networks, both within and beyond cancer. Figure 1. Figure 1. Figure 2. Figure 2. Disclosures No relevant conflicts of interest to declare.

Clinical Trial Participation Is Associated With Improved Outcome in Women With Ovarian Cancer

2009 ◽  
Vol 19 (1) ◽  
pp. 124-128 ◽  
Author(s):  
William R. Robinson ◽  
Joyce Ritter ◽  
April S. Rogers ◽  
Sean Tedjarati ◽  
Christy Lieberenz
Keyword(s):  
Ovarian Cancer ◽  
Clinical Trial ◽  
Overall Survival ◽  
Clinical Trials ◽  
Confidence Interval ◽  
Clinical Research ◽  
Trial Participation ◽  
Gynecologic Oncology Group ◽  
Histologic Subtype ◽  
Urban Versus

Objectives:To determine the effect of participation in clinical trials on survival of women with ovarian cancer. Disease-specific factors and demographics were also examined.Methods:A total of 158 women were treated for ovarian cancer at a regional cancer center. All patients were offered treatment with surgery/chemotherapy and were screened at diagnosis for participation in clinical research. Progression-free and overall survival, as well as demographic- and treatment-related data, were recorded.Results:Fifty-three participated in clinical trials and 105 did not. On-study versus off-study subjects were similar in age (64.1 vs 63.5 years), ethnicity (87% vs 85% white), performance status (100% 0-1 Gynecologic Oncology Group scale), and urban versus rural lifestyle (58% vs 55% urban). Stage of disease, histologic subtype, and type/amount of therapy were also similar. Kaplan-Meier analysis showed superior overall survival for on-study subjects (median, 46 vs 25 months, 95% confidence interval, 1.0299-2.1505 months, P = 0.0343). A trend toward improved progression-free survival approached significance for on-study subjects (median, 23 vs 9 months, 95% confidence interval, 0.9545-2.0022 months, P = 0.0866).Conclusions:Women with ovarian cancer who participate in clinical trials at this institution have improved survival compared with those who are treated with standard therapies. No other factors examined were associated with treatment completion or survival. Further, participation in clinical research does not vary by age, ethnicity, urban versus rural lifestyle, or cancer stage or histologic subtype. However, disclosure of this information to potential clinical trial participants may represent an ethical conflict and should be carefully considered in light of existing ethical guidelines for human subject research.

Oncology clinical research landscape in Middle East and North Africa (MENA) region: Challenges and proposed solutions.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e13567-e13567
Author(s):  
Kareem Sameh ◽  
Natasha Khalife
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Middle East ◽  
Clinical Research ◽  
North Africa ◽  
Research Infrastructure ◽  
Trial Participation ◽  
Mena Region ◽  
Large Patient ◽  
Oncology Clinical Trials

e13567 Background: Similar to other regions of the world, cancer incidence in Middle East and North Africa (MENA) is rising, which has been attributed to increased life expectancy and adoption of western lifestyle habits. Conducting clinical trials in the region is important to assess efficacy and safety of oncology medications in the specific population (response to drugs can be impacted by genetics, demographics and lifestyle factors). Although the MENA comprises around 5% of the global population, the region only participates in approximately 3% of clinical trials worldwide. It is important to understand the challenges in conducting trials in MENA and identify strategies to overcome these in order to facilitate advances in clinical research in the region. Methods: A literature review was conducted (via e.g. PubMed and ClinicalTrials.gov) to understand the current oncology clinical research landscape in MENA (from Jan 2015-Dec 2020), with the aim of identifying key challenges and potential strategies to overcome these. Results: Conduct of oncology clinical trials (phases 1-4) has risen in recent years in MENA, from 47 trials in 2015 to 53 trials in 2020. Despite the presence of various research-favourable factors in MENA (large patient pool, high demand for medication, lower clinical trial operational costs, compliance with ICH-GCP standards), the region still falls behind other countries in clinical research. Key factors identified as challenges in conducting clinical trials in MENA include the research infrastructure and patient awareness/understanding of research. We propose the following strategies to support the advancement of clinical research in the region: (1) Enhance research infrastructure through bolstering national clinical research networks and supporting collaboration between healthcare institutes, academia and the pharma industry; (2) Diversify methods of patient engagement (e.g. patient advisory groups and social media networks) and provide education on pros/cons of participating in research to raise awareness and improve trial participation rates; and (3) Improve availability of comprehensive oncology registries to enhance understanding of disease burden and support clinical research. Conclusions: The conduct of oncology clinical trials in MENA is increasing, yet the region is still under-represented in the global clinical trial market, despite its significant potential. The advancement of clinical research in the region will require a multi-level approach, involving collaboration between multiple stakeholders including the pharma industry, regulators, government, and healthcare professionals.

Multiple uses for a clinical research database

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 17037-17037
Author(s):  
A. O. Greco ◽  
C. M. Licavoli ◽  
L. A. White ◽  
J. R. Eckardt ◽  
K. O. Easley ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Clinical Research ◽  
Data Base ◽  
Metastatic Breast ◽  
Trial Participation ◽  
Research Database ◽  
Cooperative Group ◽  
Oncology Clinical Trials ◽  
Referring Physicians

17037 Background: In Sept 2000, the research staff at The Center for Cancer Care and Research (TCCCR) developed an excel data base to track new consults referred to the practice. It is used to identify pts for participation in Cooperative Group Clinical Trials and to identify gaps in the active protocol list. Several additional uses for the data base have evolved. Methods: Medical records provided by referring physicians for each new consult are evaluated by a Research Coordinator. Information including the pt's name, date of visit, physician, referring physician, diagnosis, protocol for which the pt is evaluated, and eligibility information is entered in the data base. Results: The data base provides a method by which we can follow pts through the protocol selection and informed consent process. Early on, the data base identified a site need for trials in metastatic breast cancer prompting us to search other sources such as the CTSU and industry. Additionally, the percentage of new consults actually enrolled on a clinical trial can be determined as well as tracking eligibility/ineligibility trends. The Pharmaceutical Research Dept can use the information to complete feasibility studies prior to participating in industry trials. The data base can be used to evaluate trends in referral patterns and has helped identify referring physicians who support our research efforts. In 2006, TCCCR had a protocol available for 45% of new consults with a cancer dx. Of those pts, 16% enrolled on a Cooperative Group Clinical Trial. According to published evaluations, 16% is well above the national average of pts who participate in oncology clinical trials. It is our assessment that TCCCR's success is due in part to the data base. Conclusions: It is well known that in order to improve treatment outcomes and diminish treatment toxicity, oncology practices and pts must participate in clinical research. It is also well known that the numbers of pts who participate in oncology clinical trials is dismal. This data base has become a valuable tool providing a method to identify and evaluate some of the reasons why pts do not enroll in clinical trials and given our practice guidance to increase pt participation. Our next goal is to evaluate the differences between the rural and urban population at TCCCR's two sites to identify additional trends in clinical trial participation. No significant financial relationships to disclose.

The Use of Digital Clinical Trial Methods in the Evaluation of Digital Therapeutics: A Scoping Review (Preprint)

2019 ◽  
Author(s):  
Allison Hirsch ◽  
Mahip Grewal ◽  
Anthony James Martorell ◽  
Brian Michael Iacoviello
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Clinical Research ◽  
Scoping Review ◽  
Digital Technologies ◽  
Good Clinical Practice ◽  
The United States ◽  
Clinical Trial Research ◽  
Digital Methods ◽  
Clinical Trial Methods

BACKGROUND Digital Therapeutics (DTx) provide evidence based therapeutic health interventions that have been clinically validated to deliver therapeutic outcomes, such that the software is the treatment. Digital methodologies are increasingly adopted to conduct clinical trials due to advantages they provide including increases in efficiency and decreases in trial costs. Digital therapeutics are digital by design and can leverage the potential of digital and remote clinical trial methods. OBJECTIVE The principal purpose of this scoping review is to review the literature to determine whether digital technologies are being used in DTx clinical research, which type are being used and whether publications are noting any advantages to their use. As DTx development is an emerging field there are likely gaps in the knowledge base regarding DTx and clinical trials, and the purpose of this review is to illuminate those gaps. A secondary purpose is to consider questions which emerged during the review process including whether fully remote digital clinical research is appropriate for all health conditions and whether digital clinical trial methods are inline with the principles of Good Clinical Practice. METHODS 1,326 records were identified by searching research databases and 1,227 reviewed at the full-article level in order to determine if they were appropriate for inclusion. Confirmation of clinical trial status, use of digital clinical research methods and digital therapeutic status as well as inclusion and exclusion criteria were applied in order to determine relevant articles. Digital methods employed in DTx research were extracted from each article and these data were synthesized in order to determine which digital methods are currently used in clinical trial research. RESULTS After applying our criteria for scoping review inclusion, 11 articles were identified. All articles used at least one form of digital clinical research methodology enabling an element of remote research. The most commonly used digital methods are those related to recruitment, enrollment and the assessment of outcomes. A small number of articles reported using other methods such as online compensation (n = 3), or digital reminders for participants (n = 5). The majority of digital therapeutics clinical research using digital methods is conducted in the United States and increasing number of articles using digital methods are published each year. CONCLUSIONS Digital methods are used in clinical trial research evaluating DTx, though not frequently as evidenced by the low proportion of articles included in this review. Fully remote clinical trial research is not yet the standard, more frequently authors are using partially remote methods. Additionally, there is tremendous variability in the level of detail describing digital methods within the literature. As digital technologies continue to advance and the clinical research DTx literature matures, digital methods which facilitate remote research may be used more frequently.

Shared-Task Worklists Improve Clinical Trial Recruitment Workflow in an Academic Emergency Department

2021 ◽  
Vol 12 (02) ◽  
pp. 293-300
Author(s):  
Kevin S. Naceanceno ◽  
Stacey L. House ◽  
Phillip V. Asaro
Keyword(s):  
Clinical Trial ◽  
Emergency Department ◽  
Clinical Trials ◽  
Clinical Research ◽  
Substantial Reduction ◽  
Text Message ◽  
High Volume ◽  
Text Messages ◽  
Shared Task ◽  
Clinical Research Coordinators

Abstract Background Clinical trials performed in our emergency department at Barnes-Jewish Hospital utilize a centralized infrastructure for alerting, screening, and enrollment with rule-based alerts sent to clinical research coordinators. Previously, all alerts were delivered as text messages via dedicated cellular phones. As the number of ongoing clinical trials increased, the volume of alerts grew to an unmanageable level. Therefore, we have changed our primary notification delivery method to study-specific, shared-task worklists integrated with our pre-existing web-based screening documentation system. Objective To evaluate the effects on screening and recruitment workflow of replacing text-message delivery of clinical trial alerts with study-specific shared-task worklists in a high-volume academic emergency department supporting multiple concurrent clinical trials. Methods We analyzed retrospective data on alerting, screening, and enrollment for 10 active clinical trials pre- and postimplementation of shared-task worklists. Results Notifications signaling the presence of potentially eligible subjects for clinical trials were more likely to result in a screen (p < 0.001) with the implementation of shared-task worklists compared with notifications delivered as text messages for 8/10 clinical trials. The change in workflow did not alter the likelihood of a notification resulting in an enrollment (p = 0.473). The Director of Research reported a substantial reduction in the amount of time spent redirecting clinical research coordinator screening activities. Conclusion Shared-task worklists, with the functionalities we have described, offer a viable alternative to delivery of clinical trial alerts via text message directly to clinical research coordinators recruiting for multiple concurrent clinical trials in a high-volume academic emergency department.

scholarly journals Are survival and mortality rates associated with recruitment to clinical trials in teenage and young adult patients with acute lymphoblastic leukaemia? A retrospective observational analysis in England

BMJ Open ◽  
2017 ◽  
Vol 7 (10) ◽  
pp. e017052 ◽  
Author(s):  
Rachael Hough ◽  
Sabrina Sandhu ◽  
Maria Khan ◽  
Anthony Moran ◽  
Richard Feltbower ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Overall Survival ◽  
Clinical Trials ◽  
Acute Lymphoblastic Leukaemia ◽  
Lymphoblastic Leukaemia ◽  
Relative Survival ◽  
Data Repository ◽  
Trial Participation ◽  
Patient Benefit ◽  
Cancer Data

ObjectiveParticipation rates in clinical trials are low in teenagers and young adults (TYA) with cancer. Whilst the importance of clinical trials in informing best practice is well established, data regarding individual patient benefit are scarce. We have investigated the association between overall survival and trial recruitment in TYA patients with acute lymphoblastic leukaemia (ALL).DesignRetrospective.SettingNational (England) TYA patients treated for ALL.Participants511 patients aged 15–24 years diagnosed with ALL between 2004 and 2010 inclusive, of whom 239 (46.7%) participated in the UKALL2003 trial.Outcome measuresPatients were identified using National Clinical Trial (UKALL2003) and Cancer Registry (National Cancer Data Repository, English National Cancer Online Registration Environment) Databases. Relative survival rates were calculated for trial and non-trial patients and observed differences were modelled using a multiple regression approach. The numbers and percentages of deaths in those patients included in the survival analysis were determined for each 3-month period, p values were calculated using the two-tailed z-test for difference between proportions and 95% CIs for percentage deaths were derived using the binomial distribution based on the Wilson Score method.ResultsPatients treated on the trial had a 17.9% better 2-year survival (85.4% vs 67.5%, p<0.001) and 8.9% better 1-year survival (90.8% vs 81.9%, p=0.004) than those not on the trial. 35 (14.6%) patients recruited to the trial died in the 2 years following diagnosis compared with 86 (32.6%) of those not recruited (p<0.001).ConclusionsTYA patients recruited to the clinical trial UKALL 2003 in England had a lower risk of mortality and a higher overall survival than contemporaneous non-trial patients. These data underline the potential for individual patient benefit in participating in a clinical trial and the importance of international efforts to increase trial participation in the TYA age group.Trial registration numberISRCTN07355119.

Disparities in clinical trials participation in a vertically integrated care delivery system.

2021 ◽  
Vol 39 (28_suppl) ◽  
pp. 128-128
Author(s):  
Ahmed Megahed ◽  
Gary L Buchschacher ◽  
Ngoc J. Ho ◽  
Reina Haque ◽  
Robert Michael Cooper
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Healthcare System ◽  
Care Delivery ◽  
Trial Participation ◽  
Cancer Type ◽  
Clinical Trial Participation ◽  
Integrated Healthcare ◽  
Clinical Trial Enrollment ◽  
Asian Pacific

128 Background: Sparse data exists on the diversity clinical trial enrollment in community settings. This information is important to ensure equity of care and generalizability of results. Methods: We conducted a retrospective cohort study of members of an integrated healthcare system diagnosed with invasive malignancies (excluding non-melanoma skin cancers) between 2013-2017 to examine demographics of the oncology population compared to those who enrolled in a clinical trial. Logistic regression was used to assess correlates of clinical trial participation, comparing general and screened samples to enrolled sample. Odds ratios were adjusted for gender, geocoded median household income, cancer type, and stage. Results: Of the 84,977 patients with a cancer diagnosis, N = 2606 were screened for clinical trial participation and consented, and of those N = 1372 enrolled. The percent of Latinx (25.8% vs 24.0%; OR 0.9? CI 0.72-1.05) and African American/Black (10.9% vs 11.1%; OR 0.92 CI 0.75-1.11) clinical trial participation mirrored that of the general oncology population, respectively using Non-Hispanic Whites as reference. Asian/Pacific Islander had equal odds of clinical trial enrollment (OR 1.08 CI 0.92-1.27). The enrolled population was younger than the general oncology population. Conclusions: This study suggests that in an integrated healthcare system with equal access to care, the clinical trials population is well representative of its general oncology population.[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 Estimands: bringing clarity and focus to research questions in clinical trials

BMJ Open ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. e052953
Author(s):  
Timothy Peter Clark ◽  
Brennan C Kahan ◽  
Alan Phillips ◽  
Ian White ◽  
James R Carpenter
Keyword(s):  
Clinical Trial ◽  
Sensitivity Analysis ◽  
Clinical Trials ◽  
Clinical Research ◽  
Recent Work ◽  
Treatment Effect ◽  
Research Question ◽  
Probability Of Success ◽  
Research Questions

Precise specification of the research question and associated treatment effect of interest is essential in clinical research, yet recent work shows that they are often incompletely specified. The ICH E9 (R1) Addendum on Estimands and Sensitivity Analysis in Clinical Trials introduces a framework that supports researchers in precisely and transparently specifying the treatment effect they aim to estimate in their clinical trial. In this paper, we present practical examples to demonstrate to all researchers involved in clinical trials how estimands can help them to specify the research question, lead to a better understanding of the treatment effect to be estimated and hence increase the probability of success of the trial.

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