Specificity of Genetic Biomarker Studies in Cancer Research: A Systematic Review.
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ABSTRACT:
SUBMITTER: Green G
PROVIDER: S-EPMC4934683 | biostudies-literature | 2016
REPOSITORIES: biostudies-literature
Publications
Specificity of Genetic Biomarker Studies in Cancer Research: A Systematic Review.
Green Garrett G Carmona Ruben R Zakeri Kaveh K Lee Chih-Han CH Borgan Saif S Marhoon Zaid Z Sharabi Andrew A Mell Loren K LK
PloS one 20160706 7
As genetic information becomes more readily available, there is increasing demand from both patients and providers to develop personalized approaches to cancer care. Investigators are increasingly reporting numbers of studies correlating genomic signatures and other biomarkers to survival endpoints. The extent to which cancer-specific and non-specific effects are reported in contemporary studies is unknown. In this review of 85 high-impact studies associating genetic biomarkers with cancer outco ...[more]
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Project description:BackgroundSensors and digital devices have revolutionized the measurement, collection, and storage of behavioral and physiological data, leading to the new term digital biomarkers.ObjectiveThis study aimed to investigate the scope of clinical evidence covered by systematic reviews (SRs) of randomized controlled trials involving digital biomarkers.MethodsThis scoping review was organized using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. With the search limited to English publications, full-text SRs of digital biomarkers included randomized controlled trials that involved a human population and reported changes in participants' health status. PubMed and the Cochrane Library were searched with time frames limited to 2019 and 2020. The World Health Organization's classification systems for diseases (International Classification of Diseases, Eleventh Revision), health interventions (International Classification of Health Interventions), and bodily functions (International Classification of Functioning, Disability, and Health [ICF]) were used to classify populations, interventions, and outcomes, respectively.ResultsA total of 31 SRs met the inclusion criteria. The majority of SRs studied patients with circulatory system diseases (19/31, 61%) and respiratory system diseases (9/31, 29%). Most of the prevalent interventions focused on physical activity behavior (16/31, 52%) and conversion of cardiac rhythm (4/31, 13%). Looking after one's health (physical activity; 15/31, 48%), walking (12/31, 39%), heart rhythm functions (8/31, 26%), and mortality (7/31, 23%) were the most commonly reported outcomes. In total, 16 physiological and behavioral data groups were identified using the ICF tool, such as looking after one's health (physical activity; 14/31, 45%), walking (11/31, 36%), heart rhythm (7/31, 23%), and weight maintenance functions (7/31, 23%). Various digital devices were also studied to collect these data in the included reviews, such as smart glasses, smartwatches, smart bracelets, smart shoes, and smart socks for measuring heart functions, gait pattern functions, and temperature. A substantial number (24/31, 77%) of digital biomarkers were used as interventions. Moreover, wearables (22/31, 71%) were the most common types of digital devices. Position sensors (21/31, 68%) and heart rate sensors and pulse rate sensors (12/31, 39%) were the most prevalent types of sensors used to acquire behavioral and physiological data in the SRs.ConclusionsIn recent years, the clinical evidence concerning digital biomarkers has been systematically reviewed in a wide range of study populations, interventions, digital devices, and sensor technologies, with the dominance of physical activity and cardiac monitors. We used the World Health Organization's ICF tool for classifying behavioral and physiological data, which seemed to be an applicable tool to categorize the broad scope of digital biomarkers identified in this review. To understand the clinical value of digital biomarkers, the strength and quality of the evidence on their health consequences need to be systematically evaluated.
| S-EPMC9641516 | biostudies-literature
Project description:In Europe, genetic counsellors are employed in specialist genetic centres or other specialist units. According to the European Board of Medical Genetics, the genetic counsellor must fulfil a range of roles, including provision of information and facilitation of psychosocial adjustment of the client to their genetic status and situation. To evaluate the extent to which genetic counsellors fulfil their prescribed roles, we conducted a systematic review of the published relevant scientific evidence. We searched five relevant electronic databases (Medline, CINAHL, SocIndex, AMED and PsychInfo) using relevant search terms and handsearched four subject-specific journals for research-based papers published in English between 1 January 2000 and 30 June 2013. Of 419 potential papers identified initially, seven satisfied the inclusion criteria for the review. Themes derived from the thematic analysis of the data were: (i) rationale for genetic counsellors to provide care, (ii) appropriate roles and responsibilities and (iii) the types of conditions included in the genetic counsellor caseload. The findings of this systematic review indicate that where genetic counsellors are utilised in specialist genetic settings, they undertake a significant workload associated with direct patient care and this appears to be acceptable to patients. With the burden on genetic services, there is an argument for the increased use of genetic counsellors in countries where they are under-utilised. In addition, roles undertaken by genetic counsellors in specialist genetic settings could be adapted to integrate genetic counsellors into multi-disciplinary teams in other specialisms.
| S-EPMC4666564 | biostudies-other
Project description:The immune system is highly dynamic and regulated by many baseline characteristic factors. As such, significant variability may exist among different patient groups suffering from the same autoimmune disease (AD). However, contemporary research practices tend to take the reductionist aggregate approach: they do not segment AD patients before embarking on biomarker discovery. This approach has been productive: many novel AD biomarkers have recently been discovered. Yet, subsequent validation studies of these biomarkers tend to suffer from a lack of specificity, sensitivity, and reproducibility which hamper their translation for clinical use. To enhance reproducibility in validation studies, an optimal discovery-phase study design is paramount: one which takes into account different parameters affecting the immune system biology. In this systematic review, we highlight need for stratification in one such parameter, i.e., sex stratification. We will first explore sex differences in immune system biology and AD prevalence, followed by reported sex-bias in the clinical phenotypes of two ADs-one which more commonly affects females: systemic lupus erythematosus, and one which more commonly affects males: ankylosing spondylitis. The practice of sex stratification in biomarker research may not only advance the discovery of sex-specific AD biomarkers but more importantly, promote reproducibility in subsequent validation studies, thus easing the translation of these novel biomarkers from bench to bedside to improve AD diagnosis. In addition, such practice will also promote deeper understanding for differential AD pathophysiology in males and females, which will be useful for the development of more effective interventions for each sex type.
| S-EPMC5994590 | biostudies-literature
Project description:BackgroundSeveral genetic association investigations have been performed over the last three decades to identify variants underlying Juvenile Myoclonic Epilepsy (JME). Here, we evaluate the accumulating findings and provide an updated perspective of these studies.MethodologyA systematic literature search was conducted using the PubMed, Embase, Scopus, Lilacs, epiGAD, Google Scholar and Sigle up to February 12, 2016. The quality of the included studies was assessed by a score and classified as low and high quality. Beyond outcome measures, information was extracted on the setting for each study, characteristics of population samples and polymorphisms.ResultsFifty studies met eligibility criteria and were used for data extraction. With a single exception, all studies used a candidate gene approach, providing data on 229 polymorphisms in or near 55 different genes. Of variants investigating in independent data sets, only rs2029461 SNP in GRM4, rs3743123 in CX36 and rs3918149 in BRD2 showed a significant association with JME in at least two different background populations. The lack of consistent associations might be due to variations in experimental design and/or limitations of the approach.ConclusionsThus, despite intense research evidence established, specific genetic variants in JME susceptibility remain inconclusive. We discussed several issues that may compromise the quality of the results, including methodological bias, endophenotype and potential involvement of epigenetic factors.Prospero registration numberCRD42016036063.
| S-EPMC5479548 | biostudies-literature
Project description:BackgroundTreatment preference research can support shared and informed decision making for currently available atopic dermatitis (AD) treatments, and simultaneously guide research and development for future therapies. In this systematic literature review, we aimed to provide an overview of preferences for AD treatments.MethodsThis systematic literature review was conducted in the Medline and Embase (via Ovid) databases, supplemented by manual searching. Quantitative research published from 2010 to September 2023 that investigated preferences for AD treatments were included. Quality assessment was conducted by using the purpose, respondents, explanation, findings, significance checklist, and a checklist developed by the Professional Society for Health Economics and Outcomes Research.ResultsIn total, 207 references were screened after removing duplicates and 15 studies were included. Most studies were conducted in the US, followed by European countries. On average, people directly or indirectly affected by AD rate efficacy and treatment-related risk as the most important criteria when choosing an AD therapy. Participants are willing to increase risks in order to have a higher chance of achieving a certain benefit, e.g. reduction in itch or clearer skin. Participants have preferences for different modes of administration. On average, 68% (all full-text studies) and 87% (only discrete choice experiments [DCEs]) of quality criteria per reference were rated as fulfilled. DCEs received generally higher quality assessment scores than non-DCEs.ConclusionsThis review revealed that AD treatment preference research is limited. Diverse study designs hampered comparison and synthesis of the results. We recommend conducting more DCEs in this field to increase the likelihood of AD patients receiving the therapy that best fits their individual needs and preferences.Clinical trials registrationThis protocol was published in PROSPERO (ID: CRD42023468757).
| S-EPMC11343911 | biostudies-literature
Project description:BackgroundOrganizational Participatory Research (OPR) seeks organizational learning and/or practice improvement. Previous systematic literature reviews described some OPR processes and outcomes, but the link between these processes and outcomes is unknown. We sought to identify and sequence the key processes of OPR taking place with and within healthcare organizations and the main outcomes to which they contribute, and to define ideal-types of OPR.MethodsThis article reports a participatory systematic mixed studies review with qualitative synthesis A specialized health librarian searched MEDLINE, CINAHL, Embase Classic + Embase, PsycINFO, the Cochrane Library, Social Work Abstracts and Business Source Complete, together with grey literature data bases were searched from inception to November 29, 2012. This search was updated using forward citation tracking up to June 2014. Reporting quality was appraised and unclear articles were excluded. Included studies clearly reported OPR where the main research related decisions were co-constructed among the academic and healthcare organization partners. Included studies were distilled into summaries of their OPR processes and outcomes, which were subsequently analysed using deductive and inductive thematic analysis. All summaries were analysed; that is, data analysis continued beyond saturation.ResultsEighty-three studies were included from the 8873 records retrieved. Eight key OPR processes were identified. Four follow the phases of research: 1) form a work group and hold meetings, 2) collectively determine research objectives, 3) collectively analyse data, and 4) collectively interpret results and decide how to use them. Four are present throughout OPR: 1) communication, 2) relationships; 3) commitment; 4) collective reflection. These processes contribute to extra benefits at the individual and organizational levels. Four ideal-types of OPR were defined. Basic OPR consists of OPR processes leading to achieving the study objectives. This ideal-type and may be combined with any of the following three ideal-types: OPR resulting in random additional benefits for the individuals or organization involved, OPR spreading to other sectors of the organization and beyond, or OPR leading to subsequent initiatives. These results are illustrated with a novel conceptual model.ConclusionThe model provides operational guidance to help OPR stakeholders collaboratively address organizational issues and achieve desired outcomes and more.Review registrationAs per PROSPERO inclusion criteria, this review is not registered.
| S-EPMC6421946 | biostudies-literature
Project description:ObjectivesTo perform a systematic review of design and reporting of imaging studies applying convolutional neural network models for radiological cancer diagnosis.MethodsA comprehensive search of PUBMED, EMBASE, MEDLINE and SCOPUS was performed for published studies applying convolutional neural network models to radiological cancer diagnosis from January 1, 2016, to August 1, 2020. Two independent reviewers measured compliance with the Checklist for Artificial Intelligence in Medical Imaging (CLAIM). Compliance was defined as the proportion of applicable CLAIM items satisfied.ResultsOne hundred eighty-six of 655 screened studies were included. Many studies did not meet the criteria for current design and reporting guidelines. Twenty-seven percent of studies documented eligibility criteria for their data (50/186, 95% CI 21-34%), 31% reported demographics for their study population (58/186, 95% CI 25-39%) and 49% of studies assessed model performance on test data partitions (91/186, 95% CI 42-57%). Median CLAIM compliance was 0.40 (IQR 0.33-0.49). Compliance correlated positively with publication year (ρ = 0.15, p = .04) and journal H-index (ρ = 0.27, p < .001). Clinical journals demonstrated higher mean compliance than technical journals (0.44 vs. 0.37, p < .001).ConclusionsOur findings highlight opportunities for improved design and reporting of convolutional neural network research for radiological cancer diagnosis.Key points• Imaging studies applying convolutional neural networks (CNNs) for cancer diagnosis frequently omit key clinical information including eligibility criteria and population demographics. • Fewer than half of imaging studies assessed model performance on explicitly unobserved test data partitions. • Design and reporting standards have improved in CNN research for radiological cancer diagnosis, though many opportunities remain for further progress.
| S-EPMC8452579 | biostudies-literature
Project description:ObjectiveLow back pain is associated with lumbar disc degeneration, which is mainly due to genetic predisposition. The objective of this study was to perform a systematic review to evaluate genetic association studies in lumbar disc degeneration as defined on magnetic resonance imaging (MRI) in humans.MethodsA systematic literature search was conducted in MEDLINE, MEDLINE In-Process, SCOPUS, ISI Web of Science, The Genetic Association Database and The Human Genome Epidemiology Network for information published between 1990-2011 addressing genes and lumbar disc degeneration. Two investigators independently identified studies to determine inclusion, after which they performed data extraction and analysis. The level of cumulative genetic association evidence was analyzed according to The HuGENet Working Group guidelines.ResultsFifty-two studies were included for review. Forty-eight studies reported at least one positive association between a genetic marker and lumbar disc degeneration. The phenotype definition of lumbar disc degeneration was highly variable between the studies and replications were inconsistent. Most of the associations presented with a weak level of evidence. The level of evidence was moderate for ASPN (D-repeat), COL11A1 (rs1676486), GDF5 (rs143383), SKT (rs16924573), THBS2 (rs9406328) and MMP9 (rs17576).ConclusionsBased on this first extensive systematic review on the topic, the credibility of reported genetic associations is mostly weak. Clear definition of lumbar disc degeneration phenotypes and large population-based cohorts are needed. An international consortium is needed to standardize genetic association studies in relation to disc degeneration.
| S-EPMC3503778 | biostudies-literature
Project description:BackgroundCallous-unemotional (CU) traits represent the affective features of psychopathy used to delineate youth at high risk for externalizing pathology. The genetic etiology CU traits is not currently well-understood.MethodsThe current review surveyed the literature for studies on the genetic underpinnings of CU traits and integrated information from 39 genetic studies.ResultsThe results from 24 studies with quantitative data suggest that the heritability for CU traits is likely between 36-67%. A majority of the 16 molecular genetic studies focused on candidate genes in the serotonin and oxytocin systems with results that have not been well replicated. Although two genome-wide association studies have been conducted, no genome-wide significant loci have been discovered.DiscussionThere is some evidence to suggest that the serotonin and oxytocin systems may play a role in CU traits; however, there is currently not enough evidence to implicate specific genetic mechanisms. The authors encourage researchers to continue to apply the most up-to-date and relevant methodology, specifically collaborations and consortiums using genome-wide and polygenic methods.
| S-EPMC6756755 | biostudies-literature
Project description:BackgroundIgnoring treatments in prognostic model development or validation can affect the accuracy and transportability of models. We aim to quantify the extent to which the effects of treatment have been addressed in existing prognostic model research and provide recommendations for the handling and reporting of treatment use in future studies.MethodsWe first describe how and when the use of treatments by individuals in a prognostic study can influence the development or validation of a prognostic model. We subsequently conducted a systematic review of the handling and reporting of treatment use in prognostic model studies in cardiovascular medicine. Data on treatment use (e.g. medications, surgeries, lifestyle interventions), the timing of their use, and the handling of such treatment use in the analyses were extracted and summarised.ResultsThree hundred two articles were included in the review. Treatment use was not mentioned in 91 (30%) articles. One hundred forty-six (48%) reported specific information about treatment use in their studies; 78 (26%) provided information about multiple treatments. Three articles (1%) reported changes in medication use ("treatment drop-in") during follow-up. Seventy-nine articles (26%) excluded treated individuals from their analysis, 80 articles (26%) modelled treatment as an outcome, and of the 155 articles that developed a model, 86 (55%) modelled treatment use, almost exclusively at baseline, as a predictor.ConclusionsThe use of treatments has been partly considered by the majority of CVD prognostic model studies. Detailed accounts including, for example, information on treatment drop-in were rare. Where relevant, the use of treatments should be considered in the analysis of prognostic model studies, particularly when a prognostic model is designed to guide the use of certain treatments and these treatments have been used by the study participants. Future prognostic model studies should clearly report the use of treatments by study participants and consider the potential impact of treatment use on the study findings.
| S-EPMC6460846 | biostudies-literature