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Eligibility Determination

Eligibility Determination is the process of assessing an individual's qualifications or suitability for participation in a research study, clinical trial, or other program.
This determination typically involves evaluating factors such as medical history, current health status, demographic characteristics, and alignment with the study or program's inclusion and exclusion criteria.
Eligibility Determination helps ensure that participants are appropriately selected and that research findings are meaningful and generalizable.
By carefully screening potential participants, this process contributes to the integrity and validity of research studies and improves the overall quality of the data collected.
Eligiblity Determination is a critical component in the design and conduct of clinical research, enabling researchers to recruit a well-suited study population and minimizing the risk of bias or confounding factors.

Most cited protocols related to «Eligibility Determination»

1
Lung Cancer Biomarkers Meta-Analysis
A Pubmed search was performed to identify lung cancer survival associated biomarkers using all combinations of the keywords “lung cancer”, “NSCLC”, “adenocarcinoma”, “squamous cell carcinoma”, “survival”, “gene expression”, “signature” and “meta analysis”. Only studies published in English were included. Eligibility criteria also included the investigation of the biomarker in at least 50 patients - biomarkers described in experimental models only were omitted. For each gene/signature the exact conditions in which it was identified have been retrieved, and these have been used as filtering when selecting the patients for the survival analysis.
To visualize the performance of the various biomarkers in datasets including different number of patients, we have generated funnel plots depicting the hazard ratio (and confidence intervals) on the horizontal axis vs. the sample size on the vertical axis for each dataset. We also added an option to the online interface to simultaneously perform the analysis in each of the individual datasets. Finally, significance was set at p<0.01.
Győrffy B., Surowiak P., Budczies J, & Lánczky A. (2013). Online Survival Analysis Software to Assess the Prognostic Value of Biomarkers Using Transcriptomic Data in Non-Small-Cell Lung Cancer. PLoS ONE, 8(12), e82241.
Publication 2013
Adenocarcinoma Biological Markers Eligibility Determination Epistropheus Gene Expression Genes Lung Lung Cancer Non-Small Cell Lung Carcinoma Patients Squamous Cell Carcinoma Tumor Markers
2
Diagnostic Accuracy of PHQ-9 for Major Depression
Datasets from articles in any language were eligible for inclusion if they included diagnostic classification for current major depressive disorder or major depressive episode on the basis of a validated semistructured or fully structured interview conducted within two weeks of PHQ-9 administration among participants aged 18 years or over who were not recruited from youth or psychiatric settings or because they were identified as having symptoms of depression. We required the diagnostic interviews and PHQ-9 to be administered within two weeks of each other because the Diagnostic and Statistical Manual of Mental Disorders (DSM) and international classification of diseases (ICD) diagnostic criteria for major depression specify that symptoms must have been present in the previous two weeks. We excluded patients from psychiatric settings and those already identified as having symptoms of depression because screening is done to identify previously unrecognized cases.
Datasets in which not all participants were eligible were included if primary data allowed selection of eligible participants. For defining major depression, we considered major depressive disorder or major depressive episode based on the DSM or ICD criteria. If more than one was reported, we prioritized major depressive episode over major depressive disorder, as screening would attempt to detect depressive episodes and further interview would determine whether the episode was related to major depressive disorder or bipolar disorder, and DSM over ICD. Across all studies, there were 23 discordant diagnoses depending on classification prioritization (0.1% of participants).
Two investigators independently reviewed titles and abstracts for eligibility. If either deemed a study potentially eligible, two investigators did full text review independently, with disagreements resolved by consensus, consulting a third investigator when necessary. We consulted translators for languages other than those in which team members were fluent.
Levis B., Benedetti A, & Thombs B.D. (2019). Accuracy of Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression: individual participant data meta-analysis. The BMJ, 365, l1476.
Publication 2019
Bipolar Disorder Depressive Symptoms Diagnosis Eligibility Determination Major Depressive Disorder Patients Youth
3
Antiretroviral Therapy in Senegal
The study was conducted from October 2011 to Jun 2012 at the Service des maladies infectieuses (SMI), located in the Centre Hospitalier National Universitaire de Fann (CHNU), Dakar, Senegal (West Africa). Upon admission and clinical examination, the eligibility of the patients enrolled in the study was established as follows: HIV/AIDS men and women at any WHO stages of the disease, under antiretroviral (ART) treatment or not, without psychiatric illness, not diabetic, without long term physical disability, and inability to eat. The study was approved by the Ethical Committee of the Ministry of Health of Senegal and registered with the National Institutes of Health as a clinical trial number NCT02433743. Prior to participation, the patients were informed about the study objectives and procedures, and their written consent was obtained.
Diouf A., Badiane A., Manga N.M., Idohou-Dossou N., Sow P.S, & Wade S. (2016). Daily consumption of ready-to-use peanut-based therapeutic food increased fat free mass, improved anemic status but has no impact on the zinc status of people living with HIV/AIDS: a randomized controlled trial. BMC Public Health, 16, 1.
Publication 2016
Acquired Immunodeficiency Syndrome Disabled Persons Eligibility Determination Mental Disorders Patients Physical Examination Woman
4
Continuous Surveillance of Heart Failure Hospitalization
Beginning in 2005, the ARIC Study conducted continuous, retrospective surveillance of hospital discharges for HF for all residents age 55 years and older in four US communities: Forsyth County, North Carolina; the city of Jackson, Mississippi; eight northwest suburbs of Minneapolis, Minnesota; and Washington County, Maryland. In 2005, there were 31 hospitals serving the four ARIC communities. The combined population in 2005 for these regions was approximately 177,000 men and women 55 years of age or older. Because of the small number of hospitalizations in the sample among race/ethnic groups other than black or white (n=55), we categorized these as white for the purposes of these analyses.
Annual electronic discharge indices were obtained from all hospitals admitting residents from the four ARIC communities. Discharges meeting eligibility criteria were sampled from these files. A hospitalization was considered eligible for validation as a HF event based on its International Classification of Disease, 9th Revision, Clinical Modification (ICD-9-CM) code, age, gender, race, and residence in the community surveillance area. Target primary or secondary hospital discharge diagnoses codes included: heart failure (428), rheumatic heart disease (398.91), hypertensive heart disease- with congestive heart failure (402.01, 402.11, 402.91), hypertensive heart disease and renal failure- with CHF (404.01, 404.03, 404.13, 404.91, 404.93), acute cor pulmonale (415.0), chronic pulmonary heart disease, unspecified (416.9), other primary cardiomyopathies (425.4), acute edema of lung, unspecified (518.4), dyspnea and respiratory abnormalities (786.0). Sampling probabilities were created to optimize variance estimates around event rate estimates with a pre-set maximum number of cases to be abstracted in 2005 of 1499 (See Supplemental Methods). This fixed number of abstractions was estimated and set based on a target number (n=500) of hospitalized events that could be investigated and validated considering available resources and time constraints. All analyses were weighted to account for the sampling probabilities.
Rosamond W.D., Chang P.P., Baggett C., Johnson A., Bertoni A.G., Shahar E., Deswal A., Heiss G, & Chambless L.E. (2012). Classification of Heart Failure in the Atherosclerosis Risk in Communities (ARIC) Study: A Comparison of Diagnostic Criteria. Circulation. Heart Failure, 5(2), 152-159.
Publication 2012
Cardiomyopathies, Primary Congenital Abnormality Cor Pulmonale Diagnosis Dyspnea Eligibility Determination Gender Heart Heart Diseases High Blood Pressures Hospitalization Kidney Failure Patient Discharge Pulmonary Edema Racial Groups Respiratory Rate Rheumatic Heart Disease Woman
5
Mapping Pilot Trials in the UK
The UKCRN database, [http://public.ukcrn.org.uk/search/ (data last accessed, 20 March 2013)] [13 ] was used to identify pilot and feasibility trials currently ongoing in the UK. The database comprises of the National Institute for Health Research (NIHR) portfolio in England, and the corresponding portfolios of Northern Ireland, Scotland and Wales. The studies benefit from the support given by the clinical research network (CRN), however, it is not compulsory for researchers to register with the UKCRN [14 ]. The database is accessible by anyone online through the URL listed above. The search was conducted on the 17th May 2012 using the key words ‘Pilot’ or ‘Feasibility’ in the title or research summary. These were the same key words used by Lancaster et al. [12 (link)] and Arain et al. [2 (link)] and were used here to maintain consistency with previous research.
The search results were exported to Excel and the studies were sorted first by primary study design in order to separate the interventional trials from the observational studies. They were then sorted by active status: in order to separate the open from the closed trials.
The open interventional trials were then assessed against the eligibility criteria as set out below. After the trials had been assessed against the inclusion criteria the eligible trials were exported into SPSS version 18.0 [15 ] for analysis.
Trials were eligible for further analysis if:
• They were randomised controlled trials;
• They were currently recruiting participants;
• They were classified as interventional;
• The participants were not healthy volunteers;
• They were not cluster randomised trials.
Trials were only included in the analysis if they were open in order to get the most up to date picture of sample sizes being used for pilot trials in the UK. Trials being conducted on healthy volunteers were not included as these are not usually efficacy studies. Cluster randomised trials were excluded from further analysis as they tend to require much larger target sample sizes (in terms of numbers of patients not clusters) than those trials which randomise patients individually. Cluster randomised trials also have different methodological issues and concerns when undertaking a pilot trial – for example to estimate the intra-class correlation (ICC).
Billingham S.A., Whitehead A.L, & Julious S.A. (2013). An audit of sample sizes for pilot and feasibility trials being undertaken in the United Kingdom registered in the United Kingdom Clinical Research Network database. BMC Medical Research Methodology, 13, 104.
Publication 2013
Compulsive Behavior Eligibility Determination Healthy Volunteers Patients

Most recents protocols related to «Eligibility Determination»

1
Ischemic Stroke Thrombolysis Protocol
We retrospectively identified consecutive patients admitted to the Stroke Unit of the University Hospital of Ancona, Italy, from January 2017 to April 2021 for acute ischemic stroke treated with IV thrombolysis. Each patient underwent routine blood sampling at admission (within 24 h of admission). Supplementary Table 1 provides an overview of the eligibility criteria.
The study was approved by the ethics committee of the Marche Polytechnic University (ID 57/2020) and conducted according to the Declaration of Helsinki. Informed consent was obtained from all subjects involved in the study or their representatives.
Norata D., Lattanzi S., Broggi S., Rocchi C., Bartolini M, & Silvestrini M. (2023). Liver fibrosis-4 score predicts outcome of patients with ischemic stroke undergoing intravenous thrombolysis. Frontiers in Neurology, 14, 1103063.
Publication 2023
Acute Ischemic Stroke Cerebrovascular Accident Eligibility Determination Ethics Committees Fibrinolytic Agents Patients
2
Cognitive Frailty and Functional Disability
Observational studies (cross-sectional or longitudinal cohort studies) were included if they reported on community-dwelling older adults aged 60 years and above. This age cutoff point was selected because studies on frailty typically included participants aged 60 years and above (27 (link)). Cross-sectional, prospective cohort studies were included due to the small number of longitudinal studies that reported on the association between cognitive frailty and disability. Cognitive frailty was defined by the presence of frailty or prefrailty, and concurrent cognitive impairment was identified using validated physical frailty and cognitive assessments. A preliminary literature search has identified that most studies on cognitive frailty have slightly modified the definition of cognitive frailty by the consensus group, defining this condition with the presence of mild cognitive impairment instead of a CDR of 0.5 with the exclusion of concurrent Alzheimer’s disease or other dementias, and physical frailty using the modified Fried frailty phenotype (28 (link)). Thus, the utilization of CDR was not compulsory for study inclusion in this review if a validated cognitive assessment tool was reported. Studies must report the association between cognitive frailty and functional disability (ADL or IADL, mobility, physical function).
Studies were excluded if they included hospitalized or institutionalized older adults or those with neurological disorders or dementia. Conference abstracts, reviews, randomized controlled trials, protocols, and studies published in other languages besides English were excluded. Study titles and abstracts were screened based on the inclusion/exclusion criteria, and full texts of relevant studies were screened for eligibility. Data were extracted using a piloted data extraction form, including study and participant characteristics, frailty assessment and classification, and corresponding disability outcomes and measurement. Data extraction was conducted by 1 reviewer (K.F.T.) and checked by the second reviewer (S.W.H.L.), with discrepancies resolved by consensus.
Tang K.F., Teh P.L, & Lee S.W. (2023). Cognitive Frailty and Functional Disability Among Community-Dwelling Older Adults: A Systematic Review. Innovation in Aging, 7(2), igad005.
Publication 2023
Aged Alzheimer's Disease Cognition Cognition Disorders Compulsive Behavior Conferences Dementia Disabled Persons Disorders, Cognitive Eligibility Determination Nervous System Disorder Phenotype Physical Examination Presenile Dementia Range of Motion, Articular
3
Recruiting Adult Outpatients for Depression
Patients between 18 and 65 years of age referred to a treatment package for single-episode depression will be recruited (Table 1) with minimal exclusion criteria to recruit representative adult outpatients who would typically receive treatment in routine practice (Table 1), of which the majority are women (71%) and aged 18–35 (68%) (S. Figure 1). Patients over 65 (approximately 0.7% of the target population) are excluded because of potential age-related cognitive decline, concomitant medical conditions, or medications that could interact with assessments or treatment (S. Figure 1). Allocation into the subcohorts is based on eligibility, e.g., MRI compatibility, scheduling, and patient willingness to participate.

Inclusion and exclusion criteria for patients

Patient inclusion criteria:

• Fulfilment of ICD-10 diagnostic criteria for a primary depressive episode (i.e., not secondary to known organic or other psychiatric disorder)

• Referral to a treatment package for single-episode depression

• Age between 18 and 65 years

Exclusion criteria:

• Psychosis or psychotic symptoms

• History of severe head trauma involving hospitalization or unconsciousness for more than 5 min

• Known, substantial structural brain abnormalities

• Insufficient Danish language skills to complete questionnaires and cognitive testing

Additional exclusion criteria for subcohort I:

• Severe somatic disease

• Contraindications for MRI (e.g., metal implants, claustrophobia, or back problems)

Additional exclusion criteria for subcohort I:

• Use of psychotropic drugs

• Exposure to radioactivity > 10 mSv within the last year

• Pregnancy or breastfeeding

The primary depressive episode, consistent with the International Statistical Classification of Diseases and Related Health Problems version 10 (ICD-10) criteria for MDD without psychotic features (F32.1, F32.2, F32.8 and F32.9), is confirmed by a specialist in psychiatry at the central diagnostic and referral centre.
Jensen K.H., Dam V.H., Ganz M., Fisher P.M., Ip C.T., Sankar A., Marstrand-Joergensen M.R., Ozenne B., Osler M., Penninx B.W., Pinborg L.H., Frokjaer V.G., Knudsen G.M, & Jørgensen M.B. (2023). Deep phenotyping towards precision psychiatry of first-episode depression — the Brain Drugs-Depression cohort. BMC Psychiatry, 23, 151.
Publication 2023
Adult Brain Claustrophobia Cognition Congenital Abnormality Craniocerebral Trauma Diagnosis Diploid Cell Disorders, Cognitive Eligibility Determination Hospitalization Mental Disorders Metals Outpatients Patients Pharmaceutical Preparations Pregnancy Psychotic Disorders Psychotropic Drugs Radioactivity Satisfaction Target Population Woman
4
Eligibility Criteria for Oesophageal Cancer Trials
The eligibility criterion for each participating trial site is the commitment to include ≥ 10 cases per year and can thus be regarded as major oesophageal cancer surgery centres [20 (link)]. This criterion is irrespective of the actual recruitment. Furthermore, all surgeons must have performed a minimum of 40 MIN-E or 40 HYBRID-E respectively to participate in the trial.
Klotz R., Diener M.K., Schmidt T., Hackert T., Graf S., Fuchs H.F., Grimminger P., Egberts J.H., Gockel I., van der Sluis P.C., Doerr-Harim C., Klose C., Feißt M, & Mihaljevic A.L. (2023). Overall morbidity after total minimally invasive keyhole oesophagectomy versus hybrid oesophagectomy (the MICkey trial): study protocol for a multicentre randomized controlled trial. Trials, 24, 175.
Publication 2023
Eligibility Determination Esophageal Cancer Hybrids Operative Surgical Procedures Surgeons
5
Evaluating IPTW for Confounding Control
We assessed the performance of propensity scores based IPTW to control for confounding by examining the distribution of baseline covariates prior and after IPT weighting, and using a threshold of 10% in standardized difference as a metric for a meaningful imbalance [25 (link)]. Using an as-treated approach, where patients were censored on treatment discontinuation or switching, we estimated the rates of the primary outcomes among patients using SGLT2i (exposure) or non-gliflozin medications (control) by calculating the number of events and incidence rates (IRs). Adjusted incidence-rate differences (RD) and hazard ratios (HR) along with their 95% confidence intervals (CIs) were modelled through weighted Cox and Poisson regressions respectively.
Sensitivity and secondary analyses were conducted to assess the robustness of the study findings. First, we examined several secondary outcomes including a composite of the two primary outcomes (i.e., HF, MI or stroke hospitalizations), as well as individually examined MI hospitalizations, stroke hospitalizations, and all-cause mortality. Second, we conducted sensitivity analyses varying exposure-related censoring criteria, where instead of censoring patients at the time of treatment switching or discontinuation, we carried the index exposure forward to mimic an intention-to-treat approach with a maximum follow up truncated to 2 years.
Third, as our primary definitions to identify HF subtypes prioritize positive predictive values at the possible cost of lowered sensitivity (i.e., under-detection of patients with HF), we also employed alternative-more sensitive-HF definitions to identify HFrEF and HFpEF patients. More specifically, we allowed patients to be included in the study if they had presence of relevant HF codes in (1) any position of the inpatient discharge diagnosis, or (2) any inpatient or outpatient diagnoses fields. Fourth, we conducted sensitivity analyses where we excluded patients with a recent hospitalization (i.e., 30-days prior to the index date). Finally, to assess impact of the study estimates across calendar time, we also estimated stratified results before and after 2016. Other eligibility criteria (e.g., no evidence of T1D) were similar for all cohorts. For all cohorts, pairwise comparisons, and sensitivity analyses, the propensity scores were re-estimated, and stabilized inverse probability of treatment weights were re-calculated. All analyses were performed using SAS 9.4 (SAS Institute Inc, Cary, NC).
Gonzalez J., Bates B.A., Setoguchi S., Gerhard T, & Dave C.V. (2023). Cardiovascular outcomes with SGLT2 inhibitors versus DPP4 inhibitors and GLP-1 receptor agonists in patients with heart failure with reduced and preserved ejection fraction. Cardiovascular Diabetology, 22, 54.
Publication 2023
Cerebrovascular Accident Diagnosis Eligibility Determination Hospitalization Hypersensitivity Inpatient Outpatients Patient Discharge Patients Pharmaceutical Preparations Sodium-Glucose Transporter 2 Inhibitors

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More about "Eligibility Determination"

Eligibility Assessment, Participant Selection, Clinical Trial Enrollment, Research Participant Screening, Subject Qualification, Enrollment Criteria, Inclusion/Exclusion Criteria, Participant Eligibility Determination, Subject Enrollment Evaluation, Clinical Research Participant Vetting, Study Population Qualification, Program Participant Suitability Assessment.
Eligibility Determination is a critical process in the design and conduct of clinical research and other programs.
It involves carefully evaluating an individual's qualifications, characteristics, and alignment with the study or program's specified criteria to ensure appropriate participant selection.
This assessment typically considers factors such as medical history, current health status, demographic information, and other relevant factors to confirm an individual's suitability for participation.
By rigorously screening potential participants, Eligibility Determination helps maintain the integrity and validity of research studies, ensuring that the findings are meaningful and generalizable.
This process contributes to high-quality data collection and minimizes the risk of bias or confounding factors that could undermine the study's conclusions.
Researchers can leverage tools like SAS version 9.4, EndNote X9, and Stata 14 to streamline the Eligibility Determination process, automate data management, and maintain accurate records of participant selection.
These software solutions can facilitate the efficient evaluation of eligibility criteria, documentation of the screening process, and integration with other research workflows.
Ultimately, Eligibility Determination is a crucial step in the research and program design process, enabling the recruitment of a well-suited study population and supporting the overall quality and reliability of the collected data.
By carefully considering an individual's qualifications, researchers can enhance the reproducibility and accuracy of their findings, contributing to the advancement of scientific knowledge and the development of effective interventions.