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European Journal of Oncology Nursing :... Jun 2023To review and critically evaluate currently available risk prediction models for breast cancer-related lymphedema (BCRL). (Meta-Analysis)
Meta-Analysis Review
PURPOSE
To review and critically evaluate currently available risk prediction models for breast cancer-related lymphedema (BCRL).
METHODS
PubMed, Embase, CINAHL, Scopus, Web of Science, the Cochrane Library, CNKI, SinoMed, WangFang Data, VIP Database were searched from inception to April 1, 2022, and updated on November 8, 2022. Study selection, data extraction and quality assessment were conducted by two independent reviewers. The Prediction Model Risk of Bias Assessment Tool was used to assess the risk of bias and applicability. Meta-analysis of AUC values of model external validations was performed using Stata 17.0.
RESULTS
Twenty-one studies were included, reporting twenty-two prediction models, with the AUC or C-index ranging from 0.601 to 0.965. Only two models were externally validated, with the pooled AUC of 0.70 (n = 3, 95%CI: 0.67 to 0.74), and 0.80 (n = 3, 95%CI: 0.75 to 0.86), respectively. Most models were developed using classical regression methods, with two studies using machine learning. Predictors most frequently used in included models were radiotherapy, body mass index before surgery, number of lymph nodes dissected, and chemotherapy. All studies were judged as high overall risk of bias and poorly reported.
CONCLUSIONS
Current models for predicting BCRL showed moderate to good predictive performance. However, all models were at high risk of bias and poorly reported, and their performance is probably optimistic. None of these models is suitable for recommendation in clinical practice. Future research should focus on validating, optimizing, or developing new models in well-designed and reported studies, following the methodology guidance and reporting guidelines.
Topics: Humans; Female; Breast Neoplasms; Lymphedema
PubMed: 37137249
DOI: 10.1016/j.ejon.2023.102326 -
Epilepsy & Behavior : E&B Apr 2016Clinical decision rules (CDRs) have been empirically demonstrated to improve patient satisfaction and enhance cost-effective care. The use of CDRs has not yet been... (Review)
Review
Clinical decision rules (CDRs) have been empirically demonstrated to improve patient satisfaction and enhance cost-effective care. The use of CDRs has not yet been robustly explored for epilepsy. We performed a systematic review of MEDLINE (from 1946) and Embase (from 1947) using Medical Subject Headings and keywords related to CDRs and epilepsy. We included original research of any language deriving, validating, or implementing a CDR using standardized definitions. Study quality was determined using a modified version of previously published criteria. A bivariate model was used to meta-analyze studies undergoing sequential derivation and validation studies. Of 2445 unique articles, 5 were determined to be relevant to this review. Three were derivation studies (three diagnostic and one therapeutic), one validation study, and one combined derivation and validation study. No implementation studies were identified. Study quality varied but was primarily of a moderate level. Two CDRs were validated and, thus, able to be meta-analyzed. Although initial measures of accuracy were high (sensitivity ~80% or above), they tended to diminish significantly in the validation studies. The pooled estimates of sensitivity and specificity both exhibited wide 95% confidence and prediction intervals that may limit their utility in routine practice. Despite the advances in therapeutic and diagnostic interventions for epilepsy, few CDRs have been developed to guide their use. Future CDRs should address common clinical scenarios such as efficient use of diagnostic tools and optimal clinical treatment decisions. Given their potential for advancing efficient, evidence-based, patient-centered healthcare, CDR development should be a priority in epilepsy.
Topics: Cost-Benefit Analysis; Decision Support Systems, Clinical; Epilepsy; Evidence-Based Medicine; Forecasting; Humans; Outcome and Process Assessment, Health Care; Patient Satisfaction; Predictive Value of Tests; Reproducibility of Results; Sensitivity and Specificity
PubMed: 26922491
DOI: 10.1016/j.yebeh.2016.01.019 -
Journal of the American Pharmacists... 2023Clinician recognition of nonadherence is generally low. Tools that clinicians have used to assess medication adherence are self-reported adherence instruments that ask... (Review)
Review
BACKGROUND
Clinician recognition of nonadherence is generally low. Tools that clinicians have used to assess medication adherence are self-reported adherence instruments that ask patients questions about their medication use experience. There is a need for more structured reviews that help clinicians comprehensively distinguish which tool might be most useful and valuable for their clinical setting and patient populations.
OBJECTIVES
This systematic review aimed to (1) identify validated, self-reported medication adherence tools that are applicable to the primary care setting and (2) summarize selected features of the tools as an assessment of clinical feasibility and applicability.
METHODS
The investigators systematically reviewed MEDLINE via Ovid, Embase via Ovid, International Pharmaceutical Abstracts, and CINAHL from inception to December 1, 2020. Investigators independently screened 3394 citations, identifying 43 articles describing validation parameters for 25 unique adherence tools. After screening each tool, 17 tools met the inclusion criteria and were qualitatively summarized.
RESULTS
Findings highlight 25 various tool characteristics (i.e., descriptions, parameters and diseases, measures and validity comparators, and other information), which clinicians might consider when selecting a self-reported adherence tool with strong measurement validity that is practical to administer to patients. There was much variability about the nature and extent of adherence measurement. Considerable variation was noted in the objective measures used to correlate to the self-reported tools' measurements. There were wide ranges of correlation between self-reported and objective measures. Several included tools had relatively low to moderate criterion validities. Many manuscripts did not describe whether tools were associated with costs, had copyrights, and were available in other languages; how much time was required for patients to complete self-report tools; and whether patient input informed tool development.
CONCLUSION
There is a critical need to ensure that adherence tool developers establish a key list of tool characteristics to report to help clinicians and researchers make practical comparisons among tools.
Topics: Humans; Self Report; Medication Adherence; Language; Primary Health Care
PubMed: 36372640
DOI: 10.1016/j.japh.2022.09.007 -
Bronchopulmonary dysplasia prediction models: a systematic review and meta-analysis with validation.Pediatric Research Jul 2023Prediction models could identify infants at the greatest risk of bronchopulmonary dysplasia (BPD) and allow targeted preventative strategies. We performed a systematic... (Meta-Analysis)
Meta-Analysis
Prediction models could identify infants at the greatest risk of bronchopulmonary dysplasia (BPD) and allow targeted preventative strategies. We performed a systematic review and meta-analysis with external validation of identified models. Studies using predictors available before day 14 of life to predict BPD in very preterm infants were included. Two reviewers assessed 7628 studies for eligibility. Meta-analysis of externally validated models was followed by validation using 62,864 very preterm infants in England and Wales. A total of 64 studies using 53 prediction models were included totalling 274,407 infants (range 32-156,587/study). In all, 35 (55%) studies predated 2010; 39 (61%) were single-centre studies. A total of 97% of studies had a high risk of bias, especially in the analysis domain. Following meta-analysis of 22 BPD and 11 BPD/death composite externally validated models, Laughon's day one model was the most promising in predicting BPD and death (C-statistic 0.76 (95% CI 0.70-0.81) and good calibration). Six models were externally validated in our cohort with C-statistics between 0.70 and 0.90 but with poor calibration. Few BPD prediction models were developed with contemporary populations, underwent external validation, or had calibration and impact analyses. Contemporary, validated, and dynamic prediction models are needed for targeted preventative strategies. IMPACT: This review aims to provide a comprehensive assessment of all BPD prediction models developed to address the uncertainty of which model is sufficiently valid and generalisable for use in clinical practice and research. Published BPD prediction models are mostly outdated, single centre and lack external validation. Laughon's 2011 model is the most promising but more robust models, using contemporary data with external validation are needed to support better treatments.
Topics: Infant; Infant, Newborn; Humans; Infant, Premature; Bronchopulmonary Dysplasia; Infant, Very Low Birth Weight; Infant, Premature, Diseases; England
PubMed: 36624282
DOI: 10.1038/s41390-022-02451-8 -
European Journal of Physical and... Jun 2023The objective of this study was to identify and review the subjective assessment tools validated in patients with fibromyalgia, identifying their most significant...
INTRODUCTION
The objective of this study was to identify and review the subjective assessment tools validated in patients with fibromyalgia, identifying their most significant structural characteristics, as well as the psychometric characteristics analyzed in each of the identified instruments.
EVIDENCE ACQUISITION
This systematic review was registered in PROSPERO with the following reference: CRD42022306878. It analyzed documents published until June 30, 2022, through the Medline, Pedro and Scopus, Dialnet, Cinahl and Latin Index databases. The keywords used were: 1) fibromyalgia; 2) assessment; 3) questionnaire; 4) reliability; 5) validity; 6) scale; and 7) validation study. Combined using the Boolean operators "AND" and "OR." The included articles were analyzed to extract: data on the structural characteristics of the questionnaires (including acronym, year of publication, number of items, sub-categories, time to complete the questionnaire, measurement range, cutoff score and cost) and psychometric characteristics of the selected questionnaires, including data on reliability (Cronbach's alpha and test-retest) and data on the validity of the questionnaires (content, construct and criterion validity).
EVIDENCE SYNTHESIS
Twenty-two studies containing 16 questionnaires were analyzed. The quality and risk of bias assessment was performed following the COSMIN checklist. In general, the quality of the subjective assessment studies validated in the population with fibromyalgia was good, with the exception of 5 studies, which did not exceed 5 points out of 10. The first questionnaire analyzed was published in 1991, and the last in 2020; the number of items ranged from 3 to 60. The most measured subcategories are function, overall impact and symptoms; other studies also include sleep and cognition disturbances. Only 6 studies described the time to complete them. The most analyzed psychometric characteristics were reliability (analyzed by 13 questionnaires), validity (analyzed by 7) and error measures (provided by only 3 of them).
CONCLUSIONS
There is a wide range of questionnaires specifically designed for patients with fibromyalgia that present good and/or excellent basic psychometric characteristics. The structural characteristics of the identified instruments were very heterogeneous, which makes it possible to select those that best adapt to the clinical/investigator scenario where the tool will be used.
Topics: Humans; Fibromyalgia; Reproducibility of Results; Surveys and Questionnaires; Psychometrics; Cognitive Dysfunction
PubMed: 37184415
DOI: 10.23736/S1973-9087.23.07762-6 -
International Journal of Environmental... Dec 2021Addressing HIV-related stigma requires the use of psychometrically sound measures. However, despite the Berger HIV stigma scale (HSS) being among the most widely used... (Review)
Review
Addressing HIV-related stigma requires the use of psychometrically sound measures. However, despite the Berger HIV stigma scale (HSS) being among the most widely used measures for assessing HIV-related stigma, no study has systematically summarised its psychometric properties. This review investigated the psychometric properties of the HSS. A systematic review of articles published between 2001 and August 2021 was undertaken (CRD42020220305) following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Additionally, we searched the grey literature and screened the reference lists of the included studies. Of the total 1241 studies that were screened, 166 were included in the review, of which 24 were development and/or validation studies. The rest were observational or experimental studies. All the studies except two reported some aspect of the scale's reliability. The reported internal consistency ranged from acceptable to excellent (Cronbach's alpha ≥ 0.70) in 93.2% of the studies. Only eight studies reported test-retest reliability, and the reported reliability was adequate, except for one study. Only 36 studies assessed and established the HSS's validity. The HSS appears to be a reliable and valid measure of HIV-related stigma. However, the validity evidence came from only 36 studies, most of which were conducted in North America and Europe. Consequently, more validation work is necessary for more precise insights.
Topics: HIV Infections; Humans; Psychometrics; Reproducibility of Results; Social Stigma; Surveys and Questionnaires
PubMed: 34948690
DOI: 10.3390/ijerph182413074 -
BMC Psychiatry Oct 2014Administrative data are increasingly used to conduct research on depression and inform health services and health policy. Depression surveillance using administrative... (Review)
Review
BACKGROUND
Administrative data are increasingly used to conduct research on depression and inform health services and health policy. Depression surveillance using administrative data is an alternative to surveys, which can be more resource-intensive. The objectives of this study were to: (1) systematically review the literature on validated case definitions to identify depression using International Classification of Disease and Related Health Problems (ICD) codes in administrative data and (2) identify individuals with and without depression in administrative data and develop an enhanced case definition to identify persons with depression in ICD-coded hospital data.
METHODS
(1) Systematic review: We identified validation studies using ICD codes to indicate depression in administrative data up to January 2013. (2) VALIDATION: All depression case definitions from the literature and an additional three ICD-9-CM and three ICD-10 enhanced definitions were tested in an inpatient database. The diagnostic accuracy of all case definitions was calculated [sensitivity (Se), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV)].
RESULTS
(1) Systematic review: Of 2,014 abstracts identified, 36 underwent full-text review and three met eligibility criteria. These depression studies used ICD-9 and ICD-10 case definitions. (2) VALIDATION: 4,008 randomly selected medical charts were reviewed to assess the performance of new and previously published depression-related ICD case definitions. All newly tested case definitions resulted in Sp >99%, PPV >89% and NPV >91%. Sensitivities were low (28-35%), but higher than for case definitions identified in the literature (1.1-29.6%).
CONCLUSIONS
Validating ICD-coded data for depression is important due to variation in coding practices across jurisdictions. The most suitable case definitions for detecting depression in administrative data vary depending on the context. For surveillance purposes, the most inclusive ICD-9 & ICD-10 case definitions resulted in PPVs of 89.7% and 89.5%, respectively. In cases where diagnostic certainty is required, the least inclusive ICD-9 and -10 case definitions are recommended, resulting in PPVs of 92.0% and 91.1%. All proposed case definitions resulted in suboptimal levels of sensitivity (ranging from 28.9%-35.6%). The addition of outpatient data (such as pharmacy records) for depression surveillance is recommended and should result in improved measures of validity.
Topics: Databases, Factual; Depression; Depressive Disorder; Humans; International Classification of Diseases; Sensitivity and Specificity
PubMed: 25322690
DOI: 10.1186/s12888-014-0289-5 -
Journal of Epidemiology and Community... May 2016Falls are a significant cause of morbidity after stroke. The aim of this review was to identify, critically appraise and summarise risk prediction models for the... (Review)
Review
BACKGROUND
Falls are a significant cause of morbidity after stroke. The aim of this review was to identify, critically appraise and summarise risk prediction models for the occurrence of falling after stroke.
METHODS
A systematic literature search was conducted in December 2014 and repeated in June 2015. Studies that used multivariable analysis to build risk prediction models for falls early after stroke were included. 2 reviewers independently assessed methodological quality. Data relating to model calibration, discrimination (C-statistic) and clinical utility (sensitivity and specificity) were extracted. A narrative review of models was conducted. PROSPERO reference: CRD42014015612.
RESULTS
The 12 included articles presented 18 risk prediction models. 7 studies predicted falls among inpatients only and 5 recorded falls in the community. Methodological quality was variable. A C-statistic was reported for 7 models and values ranged from 0.62 to 0.87. Models for use in the inpatient setting most frequently included measures of hemi-inattention, while those predicting community events included falls (or near-falls) history and balance measures most commonly. Only 2 studies reported any form of validation, and none presented a validated model with acceptable performance.
CONCLUSIONS
A number of falls-risk prediction models have been developed for use in the acute and subacute stages of stroke. Future research should focus on validating and improving existing models, with reference to the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines to ensure quality reporting and expedite clinical implementation.
Topics: Accidental Falls; Checklist; Humans; Models, Theoretical; Risk Assessment; Stroke
PubMed: 26767405
DOI: 10.1136/jech-2015-206475 -
Journal of Plastic, Reconstructive &... Nov 2022Microsurgery is a technically demanding aspect of surgery that is integral to a variety of sub-specialties. Microsurgery is required in high-risk cases where time is... (Review)
Review
BACKGROUND
Microsurgery is a technically demanding aspect of surgery that is integral to a variety of sub-specialties. Microsurgery is required in high-risk cases where time is limited and pressure is high, so there is increasing demand for skills acquisition beforehand. The aim of this review was to analyse the available literature on validated microsurgical assessment tools.
METHODS
Covidence was used to screen papers for inclusion. Keywords included 'microsurgery', 'simulation', 'end-product assessment' and 'competence'. Inclusion criteria specified simulation models which demonstrate training and assessment of skill acquisition simultaneously. Tools which were used for training independently of technical assessment were excluded and so were tools which did not include a microvascular anastomosis. Each assessment tool was evaluated for validity, bias, complexity and fidelity and reliability using PRISMA and SWiM guidelines.
RESULTS
Thirteen distinct tools were validated for use in microsurgical assessment. These can be divided into overall assessment and end-product assessment. Ten tools assessed the 'journey' of the operation, and three tools were specifically end-product assessments. All tools achieved construct validity. Criterion validity was only assessed for the UWOMSA and GRS. Interrater reliability was demonstrated for each tool except the ISSLA and SAMS. Four of the tools addressed demonstrate predictive validity. CONCLUSION: Thirteen assessment tools achieve variable validity for use in microsurgery. Interrater reliability is demonstrated for 11 of the 13 tools. The GRS and UWOMSA achieve intrarater reliability. The End Product Intimal Assessment tool and the Imperial College of Surgical Assessment device were valid tools for objective assessment of microsurgical skill.
Topics: Humans; Clinical Competence; Reproducibility of Results; Microsurgery; Anastomosis, Surgical; Computer Simulation
PubMed: 36151038
DOI: 10.1016/j.bjps.2022.06.092 -
Thyroid : Official Journal of the... Oct 2022Molecular tests for thyroid nodules with indeterminate fine needle aspiration results are increasingly used in clinical practice; however, true diagnostic summaries of... (Meta-Analysis)
Meta-Analysis Review
Molecular tests for thyroid nodules with indeterminate fine needle aspiration results are increasingly used in clinical practice; however, true diagnostic summaries of these tests are unknown. A systematic review and meta-analysis were completed to (1) evaluate the accuracy of commercially available molecular tests for malignancy in indeterminate thyroid nodules and (2) quantify biases and limitations in studies that validate those tests. PubMed, EMBASE, and Web of Science were systematically searched through July 2021. English language articles that reported original clinical validation attempts of molecular tests for indeterminate thyroid nodules were included if they reported counts of true-negative, true-positive, false-negative, and false-positive results. We performed screening and full-text review, followed by assessment of eight common biases and limitations, extraction of diagnostic and histopathological information, and meta-analysis of clinical validity using a bivariate linear mixed-effects model. Forty-nine studies were included. Meta-analysis of Afirma Gene expression classifiers (GEC; = 38 studies) revealed a sensitivity of 0.92 (confidence interval: 0.90-0.94), specificity of 0.26 (0.20-0.32), negative likelihood ratio (LR-) of 0.32 (0.23-0.44), positive LR+ of 1.24 (1.15-1.35), and area under the curve (AUC) of 0.83 (0.74-0.89). Afirma Genomic Sequencing Classifier (GSC; = 10) had a sensitivity of 0.94 (0.89-0.96), specificity of 0.38 (0.27-0.50), LR- of 0.18 (0.10-0.30), LR+ of 1.52 (1.28-1.87), and AUC of 0.91 (0.62-0.92). ThyroSeq v1 and v2 ( = 10) had a sensitivity of 0.86 (0.82-0.90), specificity of 0.74 (0.59-0.85), LR- of 0.19 (0.13-0.26), LR+ of 3.52 (2.08-5.92), and AUC of 0.86 (0.81-0.90). ThyroSeq v3 ( = 6) had a sensitivity of 0.92 (0.86-0.95), specificity of 0.41 (0.18-0.69), LR- of 0.24 (0.09-0.62), LR+ of 1.67 (1.09-2.98), and AUC of 0.90 (0.63-0.92). Fourteen percent of studies conducted a blinded histopathologic review of excised thyroid nodules, and 8% made the decision to go to surgery blind to molecular test results. Meta-analyses reveal a high diagnostic accuracy of molecular tests for thyroid nodule assessment of malignancy risk; however, these studies are subject to several limitations. Limitations and their potential clinical impacts must be addressed and, when feasible, adjusted for using valid statistical methodologies.
Topics: Humans; Thyroid Nodule; Pathology, Molecular; Biopsy, Fine-Needle; Molecular Diagnostic Techniques; Bias; Thyroid Neoplasms
PubMed: 35999710
DOI: 10.1089/thy.2022.0269