scholarly journals Analysis of Not Structurable Oncological Study Eligibility Criteria for Improved Patient-Trial Matching

2021 ◽  
Author(s):  
Friederike Dominick ◽  
Julia Dieter ◽  
Alexander Knurr ◽  
Janko Ahlbrandt ◽  
Frank Ückert
Keyword(s):  
Clinical Trial ◽  
Cancer Survival ◽  
Medical Knowledge ◽  
Patient Characteristics ◽  
Eligibility Criterion ◽  
Exclusion Criteria ◽  
Eligibility Criteria ◽  
Main Category ◽  
Diagnosis Therapy ◽  
Common Content

Abstract Background Higher enrolment rates of cancer patients into clinical trials are necessary to increase cancer survival. As a prerequisite, an improved semiautomated matching of patient characteristics with clinical trial eligibility criteria is needed. This is based on the computer interpretability, i.e., structurability of eligibility criteria texts. To increase structurability, the common content, phrasing, and structuring problems of oncological eligibility criteria need to be better understood. Objectives We aimed to identify oncological eligibility criteria that were not possible to be structured by our manual approach and categorize them by the underlying structuring problem. Our results shall contribute to improved criteria phrasing in the future as a prerequisite for increased structurability. Methods The inclusion and exclusion criteria of 159 oncological studies from the Clinical Trial Information System of the National Center for Tumor Diseases Heidelberg were manually structured and grouped into content-related subcategories. Criteria identified as not structurable were analyzed further and manually categorized by the underlying structuring problem. Results The structuring of criteria resulted in 4,742 smallest meaningful components (SMCs) distributed across seven main categories (Diagnosis, Therapy, Laboratory, Study, Findings, Demographics, and Lifestyle, Others). A proportion of 645 SMCs (13.60%) was not possible to be structured due to content- and structure-related issues. Of these, a subset of 415 SMCs (64.34%) was considered not remediable, as supplementary medical knowledge would have been needed or the linkage among the sentence components was too complex. The main category “Diagnosis and Study” contained these two subcategories to the largest parts and thus were the least structurable. In the inclusion criteria, reasons for lacking structurability varied, while missing supplementary medical knowledge was the largest factor within the exclusion criteria. Conclusion Our results suggest that further improvement of eligibility criterion phrasing only marginally contributes to increased structurability. Instead, physician-based confirmation of the matching results and the exclusion of factors harming the patient or biasing the study is needed.

scholarly journals Exclusion Criteria of Breast Cancer Clinical Trial Protocols: A Descriptive Analysis

2021 ◽  
Author(s):  
Clara Wan ◽  
Nicole E. Caston ◽  
Stacey A. Ingram ◽  
Gabrielle B. Rocque
Keyword(s):  
Heart Failure ◽  
Cardiovascular Disease ◽  
Clinical Trial ◽  
Congestive Heart Failure ◽  
Descriptive Analysis ◽  
Comorbid Conditions ◽  
Cns Metastases ◽  
Exclusion Criteria ◽  
Eligibility Criteria ◽  
Laboratory Values

Abstract Purpose3% of US adults with cancer are enrolled in a clinical trial due to various barriers to enrollment. The purpose of this study is to evaluate the variability of eligibility criteria, which currently have no standard guidelines. MethodsThis descriptive analysis utilized all therapeutic breast protocols offered at the University of Alabama at Birmingham between 2004-2020. Exclusion criteria were abstracted using OnCore and ClinicalTrials.gov. Laboratory values included liver function tests and hematologic labs. Comorbid conditions included congestive heart failure, cardiovascular disease, central nervous system (CNS) metastases, and prior cancer history. Comorbid conditions were further analyzed by amount of time protocols required participants to be from diagnosis or exacerbation-free. Results102 protocols were eligible. Among liver laboratory values, bilirubin (78%) was included in most protocols ranging from institutional upper limit of normal (ULN) (9%) to 3xULN (2%), with 1.5xULN (56%) being most common. Similar variability was observed in alanine transaminase and aspartate transaminase. Among hematological labs, 82% of protocols defined a lower limit of acceptable absolute neutrophil count ranging from 500μL (1%) to 1,800μL (1%), with 1,500μL (64%) being most common. Of the comorbid conditions, exclusion criteria varied for congestive heart failure (49%), an acute exacerbation of cardiovascular disease (80%), CNS metastases (59%) and a prior cancer (66%). The allowable timeframe varied between protocols for cardiovascular disease and prior cancer. ConclusionSubstantial heterogeneity was observed across laboratory values and comorbid variables among protocols. Future research should focus on defining standardized eligibility criteria while allowing for deviation based on drug specificity.

119 A Descriptive Epidemiological Study of Clinical Trials, Comparing Trials Targeted At Older People to Adults of All Ages

2021 ◽  
Vol 50 (Supplement_1) ◽  
pp. i12-i42
Author(s):  
J P Renton ◽  
D McAllister
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Adverse Events ◽  
Older People ◽  
Exclusion Criterion ◽  
Trial Participation ◽  
Exclusion Criteria ◽  
Eligibility Criteria ◽  
Serious Adverse Events ◽  
Icd 10

Abstract Introduction Fewer clinical trials are carried out in older people. It is unclear how representative and applicable clinical trials carried out exclusively in older people are. We compared clinical trials recruiting older people exclusively “older trials” to those recruiting adults of all ages “all age trials”, using anti-hypertensives acting on the renin-angiotensin aldosterone system (RAAS drugs) as an exemplar. Method We searched the US clinical trials register 1, to identify all trials carried out exclusively in those aged over 60. From these we selected trials of RAAS drugs. These were matched in a 2:1 ratio to trials carried out in adults of all ages. Data regarding baseline characteristics, adverse events and eligibility criteria were collected from clinical trial reports and clinicaltrials.gov. Estimated associations were calculated for age, sex and adverse events. Eligibility criteria were described and ICD- 10 coded, as appropriate. Results 71 clinical trials were carried out exclusively in older people.13 related to RAAS drugs. Participants in “Older trials” had higher mean age (73.1 and 55.9 respectively), mean difference 16.17 (CI 15.31–17.02). Older trials had fewer male participants. Participants in older trials had lower mean body mass index (BMI). A higher rate of participants in older trials experienced serious adverse events. (2.07, CI 1.55–2.75.) Few older trials had upper age limits (23.1% V 27% all age trials). All trials had exclusion criteria in multiple ICD blocks. Concurrent medications were a more common exclusion criterion in older trials (61.5% v 40.9%). Conclusions Clinical trials carried out exclusively in older people are representative in terms of age, serious adverse events and eligibility. Although there are multiple exclusion criteria for clinical trial participation in both groups, this is not prohibitive. This supports carrying out more trials exclusively in older people. References 1. NIH, US national library of medicine.ClinicalTrials.gov Available at https://clinicaltrials.gov/

scholarly journals Real-world effects of ACE inhibitors and Angiotensin Receptor Blockers: protocol for an emulation study of the ONTARGET trial using electronic health records

2021 ◽  
Author(s):  
Paris Baptiste ◽  
Angel YS Wong ◽  
Anna Schultze ◽  
Marianne Cunnington ◽  
Johannes FE Mann ◽  
...  
Keyword(s):  
Primary Care ◽  
Clinical Trial ◽  
Clinical Trials ◽  
Cohort Study ◽  
Treatment Effects ◽  
Dual Therapy ◽  
List Type ◽  
Exclusion Criteria ◽  
Eligibility Criteria ◽  
Specific Effects

ABSTRACTIntroductionCardiovascular disease (CVD) is a leading cause of death globally, responsible for nearly 18 million deaths worldwide in 2017. Medications to reduce the risk of cardiovascular events are prescribed based upon evidence from clinical trials which explore treatment effects in an indicated sample of the general population. However, these results may not be fully generalisable because of trial eligibility criteria that generally restrict to younger patients with fewer comorbidities. Therefore, evidence of effectiveness of medications for groups underrepresented in clinical trials such as those over 75 years, from ethnic minority backgrounds or with low kidney function may be limited.The ONTARGET trial studied the effects of an angiotensin-converting-enzyme (ACE) inhibitor and an angiotensin II receptor blocker (ARB) separately and in combination on cardiovascular event reduction. Using individual anonymised data from this study, in collaboration with the original trial investigators, we aim to investigate clinical trial replicability within routinely-collected patient data. If the original trial results are replicable, we will assess treatment effects and risk in groups underrepresented and excluded from the original clinical trial.Methods and analysisWe will develop a cohort analogous to the ONTARGET trial within CPRD between 1 January 2001 to 31 July 2019 using the trial eligibility criteria and propensity score matching. The primary outcome, as in the trial, is a composite of cardiovascular death, non-fatal MI, non-fatal stroke and hospitalisation for congestive heart-failure, examined in a time-to-event analysis. If results from the cohort study fall within pre-specified limits, we will expand the cohort to include those with advanced kidney dysfunction and increase the proportion of elderly participants and those from ethnicity minority backgrounds.We will then compare the risk of adverse events and association with long-term outcomes in the clinical trial, with that seen in a directly comparable sample of those attending NHS primary care.STRENGTHS AND LIMITATIONSStrengthsLarge cohort study giving power to look at effects within subgroups underrepresented in the clinical trialAccess to individual patient level data from a landmark trial to support creation of a trial-analogous cohortNovelty of studying treatment effects of dual therapy in real-world settingsLimitationsThere may be differences between the trial population and the observational cohort due to the level of detail on inclusion/exclusion criteria provided by the trialDrug-specific effects are unlikely to be able to be investigated due to small numbers in the dual-therapy arm: class-specific effects will be studied insteadMisclassification by primary care coding may lead to inaccurate replication of trial inclusion and exclusion criteria.

Cognitive technology addressing optimal cancer clinical trial matching and protocol feasibility in a community cancer practice.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 6501-6501 ◽  
Author(s):  
J. Thaddeus Beck ◽  
Michael Vinegra ◽  
Irene Dankwa-Mullan ◽  
Adam Torres ◽  
Courtney C Simmons ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Clinical Trial ◽  
Language Processing ◽  
Patient Characteristics ◽  
Cognitive Computing ◽  
Breast Cancer Patients ◽  
Exclusion Criteria ◽  
Staff Members ◽  
Ibm Watson ◽  
Oncology Practice

6501 Background: IBM Watson for Clinical Trial Matching (CTM) is a cognitive computing solution that uses natural language processing (NLP) to help increase the efficiency and accuracy of the clinical trial matching process. This solution helps providers locate suitable protocols for their patients by reading the trial criteria and matching it to the structured and unstructured patient characteristics when integrated with the Electronic Medical Record (EMR). It is also designed to determine which sites have the most viable patient population and identify inclusion and exclusion criteria that limit enrollment. Methods: This project was a collaboration among Highlands Oncology Group (HOG), Novartis and IBM Watson Health to explore the use of CTM in a community oncology practice. HOG is in Northeast Arkansas and has 15 physicians and 310 staff members working across 3 sites. During the 16-week pilot period, data from 2,620 visits by lung and breast cancer patients were processed by the CTM system. Using NLP capabilities, CTM read the clinical trial protocols provided by Novartis, and evaluated the patient data against the protocols’ inclusion and exclusion criteria. Watson excluded ineligible patients, determined those that needed further screening, and assisted in that process. Feedback on the user experience was also obtained. Results: In an initial pre-screening test, the HOG clinical trial coordinator (CTC) took 1 hour and 50 minutes to process 90 patients against 3 breast cancer protocols. Conversely, when the CTM screening solution was used, it took 24 minutes. This represents a significant reduction in time of 86 minutes or 78%. Watson excluded 94% of the patients automatically, providing criteria level evidence regarding the reason for exclusion, thus reducing the screening workload dramatically. Conclusions: IBM Watson CTM can help expedite the screening of patient charts for clinical trial eligibility and therefore may also help determine the feasibility of protocols to optimize site selection and enable higher and more efficient trial accruals.

scholarly journals Exclusion Criteria of Breast Cancer Clinical Trial Protocols: A Descriptive Analysis

2021 ◽  
Author(s):  
Clara Wan ◽  
Nicole E. Caston ◽  
Stacey A. Ingram ◽  
Gabrielle B. Rocque
Keyword(s):  
Heart Failure ◽  
Cardiovascular Disease ◽  
Clinical Trial ◽  
Congestive Heart Failure ◽  
Descriptive Analysis ◽  
Comorbid Conditions ◽  
Cns Metastases ◽  
Exclusion Criteria ◽  
Eligibility Criteria ◽  
Laboratory Values

Abstract Purpose: 3-8% of US adults with cancer are enrolled in a clinical trial due to various barriers to enrollment. The purpose of this study is to evaluate the variability of eligibility criteria, which currently have no standard guidelines.Methods: This descriptive analysis utilized all therapeutic breast protocols offered at the University of Alabama at Birmingham between 2004-2020. Exclusion criteria were abstracted using OnCore and ClinicalTrials.gov. Laboratory values included liver function tests and hematologic labs. Comorbid conditions included congestive heart failure, cardiovascular disease, central nervous system (CNS) metastases, and prior cancer history. Comorbid conditions were further analyzed by amount of time protocols required participants to be from diagnosis or exacerbation-free.Results: 102 protocols were eligible. Among liver laboratory values, bilirubin (78%) was included in most protocols ranging from institutional upper limit of normal (ULN) (9%) to 3xULN (2%), with 1.5xULN (56%) being most common. Similar variability was observed in alanine transaminase and aspartate transaminase. Among hematological labs, 82% of protocols defined a lower limit of acceptable absolute neutrophil count ranging from 500μL (1%) to 1,800μL (1%), with 1,500μL (64%) being most common. Of the comorbid conditions, exclusion criteria varied for congestive heart failure (49%), an acute exacerbation of cardiovascular disease (80%), CNS metastases (59%) and a prior cancer (66%). The allowable timeframe varied between protocols for cardiovascular disease and prior cancer.Conclusion: Substantial heterogeneity was observed across laboratory values and comorbid variables among protocols. Future research should focus on defining standardized eligibility criteria while allowing for deviation based on drug specificity.

scholarly journals Impact of prior malignancies on outcome of colorectal cancer; revisiting clinical trial eligibility criteria

BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Muneer J. Al-Husseini ◽  
Anas M. Saad ◽  
Hadeer H. Mohamed ◽  
Mohamad A. Alkhayat ◽  
Mohamad Bassam Sonbol ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Clinical Trial ◽  
Eligibility Criteria

scholarly journals Single-bone versus both-bone plating of unstable paediatric both-bone forearm fractures. A randomized controlled clinical trial

2021 ◽  
Author(s):  
Mohamed Khaled ◽  
Amr A. Fadle ◽  
Ahmed Khalil Attia ◽  
Andrew Sami ◽  
Abdelkhalek Hafez ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Operative Time ◽  
Forearm Fractures ◽  
Inclusion Criteria ◽  
Fracture Union ◽  
Exclusion Criteria ◽  
Bone Fixation ◽  
Fixation Group ◽  
Significant Difference ◽  
Single Bone

Abstract Purpose This clinical trial compares the functional and radiological outcomes of single-bone fixation to both-bone fixation of unstable paediatric both-bone forearm fractures. Methods This individually randomized two-group parallel clinical trial was performed following the Consolidated Standards of Reporting Trials (CONSORT) statement at a single academic tertiary medical centre with an established paediatric orthopaedics unit. All children aged between nine and 15 years who presented to the emergency department at Assiut university with unstable diaphyseal, both-bone forearm fractures requiring surgical intervention between November 1, 2018, and February 28, 2020, were screened for eligibility against the inclusion and exclusion criteria. Inclusion criteria were diaphyseal unstable fractures defined as shaft fractures between the distal and proximal metaphyses with an angulation of > 10°, and/or malrotation of > 30°, and/or displacement > 10 mm after attempted closed reduction. Exclusion criteria included open fractures, Galeazzi fractures, Monteggia fractures, radial head fractures, and associated neurovascular injuries. Patients who met the inclusion criteria were randomized to either the single-bone fixation group (intervention) or the both-bone fixation group (control). Primary outcomes were forearm range of motion and fracture union, while secondary outcomes were forearm function (price criteria), radius re-angulation, wrist and elbow range of motion, and surgical time Results A total of 50 children were included. Out of these 50 children, 25 were randomized to either arm of the study. All children in either group received the treatment assigned by randomization. Fifty (100%) children were available for final follow-up at six months post-operatively. The mean age of single-bone and both-bone fixation groups was 11.48 ± 1.93 and 13 ± 1.75 years, respectively, with a statistically significant difference (p = 0.006). There were no statistically significant differences in gender, laterality, affection of the dominant hand, or mode of trauma between single-bone and both-bone fixation groups. All patients in both groups achieved fracture union. There mean radius re-angulation of the single-bone fixation groups was 5.36 ± 4.39 (0–20) degrees, while there was no radius re-angulation in the both-bone fixation group, with a statistically significant difference (p < 0.001). The time to union in the single-bone group was 6.28 ± 1.51 weeks, while the time to union in the both-bone fixation group was 6.64 ± 1.75 weeks, with no statistically significant difference (p = 0.44). There were no infections or refractures in either group. In the single-bone fixation group, 24 (96%) patients have regained their full forearm ROM (loss of ROM < 15°), while only one (4%) patient lost between 15 and 30° of ROM. In the both-bone fixation group, 23 (92%) patients have regained their full forearm ROM (loss of ROM < 15°), while only two (8%) patients lost between 15 and 30° of ROM. There was no statistically significant difference between groups in loss of forearm ROM (p = 0.55). All patients in both groups regained full ROM of their elbow and wrist joints. On price grading, 24 (96%) and 23 (92%) patients who underwent single bone fixation and both-bone fixation scored excellent, respectively. Only one (4%) patient in the single-bone fixation group and two (8%) patients in the both-bone fixation group scored good, with no statistically significant difference in price score between groups (p = 0.49). The majority of the patients from both groups had no pain on the numerical pain scale; 22 (88%) patients in the single-bone fixation group and 21 (84%) patients in the both-bone fixation groups, with no statistically significant difference between groups (p = 0.38). The single-bone fixation group had a significantly shorter mean operative time in comparison to both-bones plating (43.60 ± 6.21 vs. 88.60 ± 10.56 (min); p < 0.001). Conclusion Single-bone ulna open reduction and plate fixation and casting are safe and had a significantly shorter operative time than both-bone fixation. However, single-bone ORIF had a higher risk radius re-angulation, alas clinically acceptable. Both groups had equally excellent functional outcomes, forearm ROM, and union rates with no complications or refractures. Long-term studies are required.

scholarly journals Assessment of automated clinical trial recruitment and enrolment using patient-facing technology

2021 ◽  
Vol 28 (1) ◽  
pp. e100076
Author(s):  
Naomi S Bardach ◽  
Regina Lam ◽  
Carolyn B Jasik
Keyword(s):  
Clinical Trial ◽  
Patient Characteristics ◽  
Electronic Signature ◽  
Study Materials ◽  
Study Staff ◽  
Surgical Units ◽  
Study Implementation ◽  
Registration Number ◽  
Care Systems ◽  
Group Comparisons

ObjectiveInteractive patient care systems (IPCS) at the bedside are becoming increasingly common, but evidence is limited as to their potential for innovative clinical trial implementation. The objective of this study was to test the hypothesis that the IPCS could feasibly be used to automate recruitment and enrolment for a clinical trial.MethodsIn medical-surgical units, we used the IPCS to randomise, recruit and consent eligible subjects. For participants not interacting with IPCS study materials within 48 hours, study staff-initiated recruitment in-person. Eligible study population included all caregivers and any patients >6 years old admitted to medical-surgical units and oncology units September 2015 to January 2016. Outcomes: randomisation assessed using between-group comparisons of patient characteristics; recruitment success assessed by rates of consent; paperless implementation using successful acquisition of electronic signature and email address. We used χ2 analysis to assess success of randomisation and recruitment.ResultsRandomisation was successful (n=1012 randomised, p>0.05 for all between-group comparisons). For the subset of eligible, randomised patients who were recruited, IPCS-only recruitment (consented: 2.4% of n=213) was less successful than in-person recruitment (61.4% of n=87 eligible recruited, p<0.001). For those consenting (n=61), 96.7% provided an electronic signature and 68.9% provided email addresses.ConclusionsOur results suggest that as a tool at the bedside, the IPCS offers key efficiencies for study implementation, including randomisation and collecting e-consent and contact information, but does not offer recruitment efficiencies. Further research could assess the value that interactive technologies bring to recruitment when paired with in-person efforts, potentially focusing on more intensive user-interface testing for recruitment materials.Trial registration numberNCT02491190.

scholarly journals Automated classification of clinical trial eligibility criteria text based on ensemble learning and metric learning

2021 ◽  
Vol 21 (S2) ◽  
Author(s):  
Kun Zeng ◽  
Yibin Xu ◽  
Ge Lin ◽  
Likeng Liang ◽  
Tianyong Hao
Keyword(s):  
Clinical Trial ◽  
Ensemble Learning ◽  
Metric Learning ◽  
Classification Performance ◽  
Ensemble Model ◽  
Automated Classification ◽  
Eligibility Criteria ◽  
Data Imbalance ◽  
The Impact

Abstract Background Eligibility criteria are the primary strategy for screening the target participants of a clinical trial. Automated classification of clinical trial eligibility criteria text by using machine learning methods improves recruitment efficiency to reduce the cost of clinical research. However, existing methods suffer from poor classification performance due to the complexity and imbalance of eligibility criteria text data. Methods An ensemble learning-based model with metric learning is proposed for eligibility criteria classification. The model integrates a set of pre-trained models including Bidirectional Encoder Representations from Transformers (BERT), A Robustly Optimized BERT Pretraining Approach (RoBERTa), XLNet, Pre-training Text Encoders as Discriminators Rather Than Generators (ELECTRA), and Enhanced Representation through Knowledge Integration (ERNIE). Focal Loss is used as a loss function to address the data imbalance problem. Metric learning is employed to train the embedding of each base model for feature distinguish. Soft Voting is applied to achieve final classification of the ensemble model. The dataset is from the standard evaluation task 3 of 5th China Health Information Processing Conference containing 38,341 eligibility criteria text in 44 categories. Results Our ensemble method had an accuracy of 0.8497, a precision of 0.8229, and a recall of 0.8216 on the dataset. The macro F1-score was 0.8169, outperforming state-of-the-art baseline methods by 0.84% improvement on average. In addition, the performance improvement had a p-value of 2.152e-07 with a standard t-test, indicating that our model achieved a significant improvement. Conclusions A model for classifying eligibility criteria text of clinical trials based on multi-model ensemble learning and metric learning was proposed. The experiments demonstrated that the classification performance was improved by our ensemble model significantly. In addition, metric learning was able to improve word embedding representation and the focal loss reduced the impact of data imbalance to model performance.

Sign in / Sign up

Export Citation Format

Share Document