Abstract 21P
Background
Clinical trial registries record the proposed and actual completion date of studies. Study duration affects budget, personnel, governance and ethics. To our knowledge, no data exists comparing estimated time to study completion with actual completion date. Using breast cancer trials as an exemplar, we analyzed differences between estimated and actual duration of clinical trials.
Methods
A sophisticated artificial intelligence (AI) tool, Risklick AI®1-3 analysed clinical trial registry fields for proposed trial completion (entered at time of study registration) compared to date entered for study completion. This technology collects and unifies trial data from all 18 public registries, including clinicaltrials.gov and WHO. The comprehensive search performed on 15.3.23 for period 2000 – 2023 used 101 keywords to cover breast cancer subtypes in completed trials. Trials were analyzed according to factors postulated to impact duration: disease extent, histological subtype, phase, number of eligibility criteria, sample size, country and sponsor. Delay was defined as the additional time required to complete the trial compared to the estimated study completion date, with a tolerance of 30 days.
Results
582 trials, involving 104’384 patients, recorded both planned and actual completion dates. Overall, 21.6% were finished early, 7.9% on time, and 70.4% had delay, of mean 31.7 +/- 25.6 months [standard deviation], ranging 1 - 155 months. The mean delay was similar for trials analysed by disease extent, breast cancer subtype, phase, number of eligibility criteria, sample size, country, or sponsor type.
Conclusions
This large real-world dataset revealed an average delay in completion of 2.5-year for 70% of breast cancer trials, independent of multiple factors commonly thought to affect trial duration. This data should be considered when planning, budgeting and setting participant and community expectations for trials. Tools to accurately predict trial duration and efforts to reduce delays are needed.
References: 1. www.risklick.ch 2. Front Digit Health. 2021;3 3. Pharmacology. 2021;106(5-6):244-253.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
University of Bern.
Funding
Has not received any funding.
Disclosure
P. Khlebnikov, F. Meer, Q. Haas: Financial Interests, Personal, Full or part-time Employment: Risklick AG. P. Amini: Financial Interests, Personal, Ownership Interest: Risklick AG. E. Segelov: Financial Interests, Personal, Invited Speaker, Limbic are a medical educational company running various seminars which I have participated in as an invited speaker/Chair: Limbic; Financial Interests, Personal, Invited Speaker, webinar on colorectal cancer 28/02/21: Servier; Financial Interests, Institutional, Local PI, As head of the Oncology Cancer clinical trials at Monash Health (until 15 Aug 2022) where there were >200 trials active, there were the usual commercial arrangements to run the trials with the institution. There was no personal financial benefit from any: > 15 different companies. All other authors have declared no conflicts of interest.
Resources from the same session
40P - Intra-tumoral CD3, CD4, and CD8 as prognostic biomarkers in Asian breast cancer
Presenter: Jia Wern Pan
Session: Poster Display
Resources:
Abstract
41P - Brown fat activation demonstrated on FDG PET/CT predicts survival outcome
Presenter: Sonya Park
Session: Poster Display
Resources:
Abstract
42P - A promising anticancer drug for triple-negative breast cancer: OZ-001 suppresses tumor growth by dual targeting STAT3 and calcium signaling
Presenter: Jisun Kim
Session: Poster Display
Resources:
Abstract
43P - Performance evaluation of a combined risk model for breast cancer risk prediction in Indonesian population (TRIP Study)
Presenter: Marco Wijaya
Session: Poster Display
Resources:
Abstract
44P - Pathological complete response to neoadjuvant chemotherapy and outcomes in Her-2 negative locally advanced breast cancer
Presenter: Amrith Patel
Session: Poster Display
Resources:
Abstract
45P - Demographic determinants of pathological complete response after neoadjuvant chemotherapy in breast cancer
Presenter: Anvesh Dharanikota
Session: Poster Display
Resources:
Abstract
46P - Predicting toxicity following cancer chemotherapy by detecting transporter gene ABCB1 (C1236T, G2677T/A, C3435CT) polymorphism in breast cancer patients receiving chemotherapy with anthracycline and taxane either sequentially or concomitantly
Presenter: Tanuma Mistry
Session: Poster Display
Resources:
Abstract
47P - Sequencing of chemotherapy and surgery among older triple-negative and HER2-positive breast cancer patients with comorbidities
Presenter: Anvesh Dharanikota
Session: Poster Display
Resources:
Abstract
48P - The impact of preoperative axillary ultrasound on the false negative rate of sentinel lymph node biopsy in post neoadjuvant chemotherapy breast cancer patients
Presenter: Byshetty Rajendar
Session: Poster Display
Resources:
Abstract
49P - Survival outcomes of HER2-positive breast cancer patients treated with neoadjuvant therapy at a single cancer centre in India
Presenter: Minit Shah
Session: Poster Display
Resources:
Abstract