Perspective

In the quiet, green countryside outside Milan, one foggy morning, a few years back, I was driving along an isolated road. There Miss Murer, one of my patients, was eagerly awaiting my arrival. But long before I was anywhere near the remote property, I was already lost. Beside me, a roughly folded map was helpfully leading me away from familiar landmarks. Inhabitants kindly provided directions, but only confused what my sense of direction had left. This was a recurrent situation in my life, until 'Sat-navs' became available. These have a clear purpose: to give complete driving directions with the least possible risk of getting lost. In a few years they have become very popular. Innovative features are offered on top of essential information: travel time between destinations, real-time traffic updates, 3D views, to name a few. Now I'm not worried any more when a patient calls me asking for a visit and proudly announces the name of a neighbourhood I never heard of. I need something similar to avoid losing my direction when a doubt comes to my mind in clinical practice: information services I can trust, that provide relevant and reliable information when I'm searching for a correct diagnosis or treatment. However, there is a vital difference: being lost does not kill people, being lost in clinical practice may do

Antiplatelet drugs for secondary prevention in patients with ischemic stroke or transient ischemic attack: a systematic review and network meta-analysis.

BACKGROUND Antiplatelet drugs may prevent recurrent ischemic events after ischemic stroke but their relative effectiveness and harms still need to be clarified. Within this network meta-analysis we aimed to summarize the current evidence for using antiplatelet drugs for secondary stroke prevention. METHODS We searched MEDLINE, EMBASE and CENTRAL up to September 2020. Randomized controlled trials (RCTs) assessing antiplatelet drugs for secondary stroke prevention were included. We did pairwise meta-analyses and network meta-analyses using random-effects models. Primary outcomes were all strokes (ischemic or hemorrhagic) and all-cause mortality. RESULTS The review included 57 RCTs, 50 (n = 165,533 participants) provided data for the meta-analyses. Compared to placebo/no treatment, moderate to high-confidence evidence indicated that cilostazol, clopidogrel, dipyridamole + aspirin, ticagrelor, ticlopidine, and aspirin ≤ 150 mg/day significantly reduced the risk of all strokes (odds ratios, ORs and absolute risk difference, ARD): cilostazol 0.51 (95 % confidence interval, CI, 0.37 to 0.71; 3.6 % fewer), clopidogrel 0.63 (95 % CI, 0.49 to 0.79; 2.7 % fewer), dipyridamole + aspirin 0.65 (95 % CI, 0.55 to 0.78; 2.5 % fewer), ticagrelor 0.68 (95 % CI, 0.50 to 0.93; 2.3 % fewer), ticlopidine 0.74 (95 % CI 0.59 to 0.93; 1.9 % fewer), aspirin ≤ 150 mg/day 0.79 (95 % CI, 0.66 to 0.95; 1.5 % fewer). Aspirin > 150 mg/day and the combinations clopidogrel/aspirin, ticagrelor/aspirin, also decrease all strokes but increase the risk of hemorrhagic events. Only aspirin > 150 mg/day significantly reduced all-cause mortality (OR 0.86, 95 % CI 0.76 to 0.97; ARD 0.9 %, 95 %CI 1.5-0.2 % fewer, moderate confidence). Compared to aspirin ≤ 150 mg/day, clopidogrel significantly reduced the risk of all strokes, cardiovascular events, and intracranial hemorrhage outcomes. Cilostazol also appeared to provide advantages but data are limited to the Asian population. CONCLUSIONS Considering the benefits and harms ratio, cilostazol, clopidogrel, dipyridamole + aspirin, ticagrelor, ticlopidine, and aspirin ≤ 150 mg/day appear to be the best choices as antiplatelet drugs for secondary prevention of patients with ischemic stroke or TIA. SYSTEMATIC REVIEW REGISTRATION PROSPERO CRD42020159896

Speed of updating online evidence based point of care summaries: prospective cohort analysis

Objective To evaluate the ability of international point of care information summaries to update evidence relevant to medical practice

Switching among biosimilars : a review of clinical evidence

Biological medicines have improved patients' outcomes, but their high costs may limit access. Biosimilars, alternatives which have demonstrated high similarity in terms of quality, safety and efficacy to an already licensed originator biological product, could increase competition and decrease prices. Given the expanding number of biosimilars, patients may switch from originator to biosimilar or among biosimilars. Randomized trials and observational studies conducted with multiple biosimilars over many disease areas confirmed the safety and efficacy of switching from originator to biosimilar. This study summarizes evidence on switching between biosimilars for which there are concerns to provide future guidance. Systematic search (Medline, Embase, Cochrane Library) for studies on anti-TNF agents, assessing clinical efficacy and safety of biosimilar-to-biosimilar switch in chronic inflammatory diseases. We retrieved 320 records and included 19 clinical studies. One study with historical control compared switching between biosimilars to maintenance of the same biosimilar. Ten were controlled cohort studies comparing switching between two biosimilars vs switching from originator to a biosimilar or vs multiple switches. Eight were single-arm cohort studies, where participants switched from one biosimilar to another and the outcomes were compared before and after the switch. Overall, these studies did not highlight significant concerns in switching between biosimilars. Therefore, switching studies seem difficult to perform and unnecessary with the body of evidence suggesting no real problems in practice coupled with stringent regulatory requirements. Monitoring the use of biosimilars in clinical practice could support clinical decision making, rational use of biologic medicines, and help to further realize possible savings

Evaluating Translational Methods for Personalized Medicine—A Scoping Review

The introduction of personalized medicine, through the increasing multi-omics characterization of disease, brings new challenges to disease modeling. The scope of this review was a broad evaluation of the relevance, validity, and predictive value of the current preclinical methodologies applied in stratified medicine approaches. Two case models were chosen: oncology and brain disorders. We conducted a scoping review, following the Joanna Briggs Institute guidelines, and searched PubMed, EMBASE, and relevant databases for reports describing preclinical models applied in personalized medicine approaches. A total of 1292 and 1516 records were identified from the oncology and brain disorders search, respectively. Quantitative and qualitative synthesis was performed on a final total of 63 oncology and 94 brain disorder studies. The complexity of personalized approaches highlights the need for more sophisticated biological systems to assess the integrated mechanisms of response. Despite the progress in developing innovative and complex preclinical model systems, the currently available methods need to be further developed and validated before their potential in personalized medicine endeavors can be realized. More importantly, we identified underlying gaps in preclinical research relating to the relevance of experimental models, quality assessment practices, reporting, regulation, and a gap between preclinical and clinical research. To achieve a broad implementation of predictive translational models in personalized medicine, these fundamental deficits must be addressed.publishedVersio

Biomarker discovery studies for patient stratification using machine learning analysis of omics data: a scoping review

Objective: To review biomarker discovery studies using omics data for patient stratification which led to clinically validated FDA-cleared tests or laboratory developed tests, in order to identify common characteristics and derive recommendations for future biomarker projects. Design: Scoping review. Methods: We searched PubMed, EMBASE and Web of Science to obtain a comprehensive list of articles from the biomedical literature published between January 2000 and July 2021, describing clinically validated biomarker signatures for patient stratification, derived using statistical learning approaches. All documents were screened to retain only peer-reviewed research articles, review articles or opinion articles, covering supervised and unsupervised machine learning applications for omics-based patient stratification. Two reviewers independently confirmed the eligibility. Disagreements were solved by consensus. We focused the final analysis on omics-based biomarkers which achieved the highest level of validation, that is, clinical approval of the developed molecular signature as a laboratory developed test or FDA approved tests. Results: Overall, 352 articles fulfilled the eligibility criteria. The analysis of validated biomarker signatures identified multiple common methodological and practical features that may explain the successful test development and guide future biomarker projects. These include study design choices to ensure sufficient statistical power for model building and external testing, suitable combinations of non-targeted and targeted measurement technologies, the integration of prior biological knowledge, strict filtering and inclusion/exclusion criteria, and the adequacy of statistical and machine learning methods for discovery and validation. Conclusions: While most clinically validated biomarker models derived from omics data have been developed for personalised oncology, first applications for non-cancer diseases show the potential of multivariate omics biomarker design for other complex disorders. Distinctive characteristics of prior success stories, such as early filtering and robust discovery approaches, continuous improvements in assay design and experimental measurement technology, and rigorous multicohort validation approaches, enable the derivation of specific recommendations for future studies

Methods for Stratification and Validation Cohorts: A Scoping Review

Personalized medicine requires large cohorts for patient stratification and validation of patient clustering. However, standards and harmonized practices on the methods and tools to be used for the design and management of cohorts in personalized medicine remain to be defined. This study aims to describe the current state-of-the-art in this area. A scoping review was conducted searching in PubMed, EMBASE, Web of Science, Psycinfo and Cochrane Library for reviews about tools and methods related to cohorts used in personalized medicine. The search focused on cancer, stroke and Alzheimer's disease and was limited to reports in English, French, German, Italian and Spanish published from 2005 to April 2020. The screening process was reported through a PRISMA flowchart. Fifty reviews were included, mostly including information about how data were generated (25/50) and about tools used for data management and analysis (24/50). No direct information was found about the quality of data and the requirements to monitor associated clinical data. A scarcity of information and standards was found in specific areas such as sample size calculation. With this information, comprehensive guidelines could be developed in the future to improve the reproducibility and robustness in the design and management of cohorts in personalized medicine studies

Effectiveness of a Hospital-Based Computerized Decision Support System on Clinician Recommendations and Patient Outcomes: A Randomized Clinical Trial.

IMPORTANCE: Sophisticated evidence-based information resources can filter medical evidence from the literature, integrate it into electronic health records, and generate recommendations tailored to individual patients. OBJECTIVE: To assess the effectiveness of a computerized clinical decision support system (CDSS) that preappraises evidence and provides health professionals with actionable, patient-specific recommendations at the point of care. DESIGN, SETTING, AND PARTICIPANTS: Open-label, parallel-group, randomized clinical trial among internal medicine wards of a large Italian general hospital. All analyses in this randomized clinical trial followed the intent-to-treat principle. Between November 1, 2015, and December 31, 2016, patients were randomly assigned to the intervention group, in which CDSS-generated reminders were displayed to physicians, or to the control group, in which reminders were generated but not shown. Data were analyzed between February 1 and July 31, 2018. INTERVENTIONS: Evidence-Based Medicine Electronic Decision Support (EBMEDS), a commercial CDSS covering a wide array of health conditions across specialties, was integrated into the hospital electronic health records to generate patient-specific recommendations. MAIN OUTCOMES AND MEASURES: The primary outcome was the resolution rate, the rate at which medical problems identified and alerted by the CDSS were addressed by a change in practice. Secondary outcomes included the length of hospital stay and in-hospital all-cause mortality. RESULTS: In this randomized clinical trial, 20 563 patients were admitted to the hospital. Of these, 6480 (31.5%) were admitted to the internal medicine wards (study population) and randomized (3242 to CDSS and 3238 to control). The mean (SD) age of patients was 70.5 (17.3) years, and 54.5% were men. In total, 28 394 reminders were generated throughout the course of the trial (median, 3 reminders per patient per hospital stay; interquartile range [IQR], 1-6). These messages led to a change in practice in approximately 4 of 100 patients. The resolution rate was 38.0% (95% CI, 37.2%-38.8%) in the intervention group and 33.7% (95% CI, 32.9%-34.4%) in the control group, corresponding to an odds ratio of 1.21 (95% CI, 1.11-1.32; P < .001). The length of hospital stay did not differ between the groups, with a median time of 8 days (IQR, 5-13 days) for the intervention group and a median time of 8 days (IQR, 5-14 days) for the control group (P = .36). In-hospital all-cause mortality also did not differ between groups (odds ratio, 0.95; 95% CI, 0.77-1.17; P = .59). Alert fatigue did not differ between early and late study periods. CONCLUSIONS AND RELEVANCE: An international commercial CDSS intervention marginally influenced routine practice in a general hospital, although the change did not statistically significantly affect patient outcomes. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT02577198

Grading of recommendations, assessment, development and evaluations concept 7: issues and insights linking guideline recommendations to trustworthy essential medicine lists

Objectives: Guidelines and essential medicine lists (EMLs) bear similarities and differences in the process that lead to decisions. Access to essential medicines is central to achieve universal health coverage. The World Health Organization (WHO) EML has guided prioritization of essential medicines globally for nearly 50 years, and national EMLs (NEMLs) exist in over 130 countries. Guideline and EML decisions, at WHO or national levels, are not always coordinated and aligned. We sought to explore challenges, and potential solutions, for decision-making to support trustworthy medicine selection for EMLs from a Grading of Recommendations, Assessment, Development and Evaluations (GRADE) Working Group perspective. We primarily focus on the WHO EML; however, our findings may be applicable to NEML decisions as well. Study Design and Setting: We identified key challenges in connecting the EML to health guidelines by involving a broad group of stakeholders and assessing case studies including real applications to the WHO EML, South Africa NEML, and a multiple sclerosis guideline connected to a WHO EML application for multiple sclerosis treatments. To address challenges, we utilized the results of a survey and feedback from the stakeholders, and iteratively met as a project group. We drafted a conceptual framework of challenges and potential solutions. We presented a summary of the results for feedback to all attendees of the GRADE Working Group meetings in November 2022 (approximately 120 people) and in May 2023 (approximately 100 people) before finalizing the framework. Results: We prioritized issues and insights/solutions that addressed the connections between the EML and health guidelines. Our suggested solutions include early planning alignment of guideline groups and EMLs, considering shared participation to strengthen linkage, further clarity on price/cost considerations, and using explicit shared criteria to make guideline and EML decisions. We also provide recommendations to strengthen the connection between WHO EML and NEMLs including through contextualization methods. Conclusion: This GRADE concept article, jointly developed by key stakeholders from the guidelines and EMLs field, identified key conceptual issues and potential solutions to support the continued advancement of trustworthy EMLs. Adopting structured decision criteria that can be linked to guideline recommendations bears the potential to advance health equity and gaps in availability of essential medicines within and between countries

Klinička praksa temeljena na dokazima: pregled prijetnji valjanosti dokaza i kako ih spriječiti

Using the best quality of clinical research evidence is essential for choosing the right treatment for patients. How to identify the best research evidence is, however, difficult. In this narrative review we summarise these threats and describe how to minimise them. Pertinent literature was considered through literature searches combined with personal files. Treatments should generally not be chosen based only on evidence from observational studies or single randomised clinical trials. Systematic reviews with meta-analysis of all identifiable randomised clinical trials with Grading of Recommendations Assessment, Development and Evaluation (GRADE) assessment represent the highest level of evidence. Even though systematic reviews are trust worthier than other types of evidence, all levels of the evidence hierarchy are under threats from systematic errors (bias); design errors (abuse of surrogate outcomes, composite outcomes, etc.); and random errors (play of chance). Clinical research infrastructures may help in providing larger and better conducted trials. Trial Sequential Analysis may help in deciding when there is sufficient evidence in meta-analyses. If threats to the validity of clinical research are carefully considered and minimised, research results will be more valid and this will benefit patients and heath care systems.Primjena najkvalitetnijih dokaza kliničkih istraživanja ključna je u odabiru ispravnog liječenja pacijenata. No, način na koji će se odabrati najbolji dokazi predstavlja često poteškoću. Ovim preglednim člankom prikazujemo opasnosti navedenog odabira, kao i načine kako ih umanjiti. Relevantni izvori razmatrani su pretragom literature u kombinaciji s osobnim datotekama. Izbor liječenja uglavnom se ne bi smio temeljiti isključivo na opservacijskim ili pojedinačnim randomiziranim kliničkim studijama. Sustavni pregledi s metaanalizom svih identificiranih randomiziranih kliničkih studija procijenjenih sustavom stupnjevanja procjene, razvoja i evaluacije preporuka (engl. Grading of Recommendations Assessment, Development and Evaluation; GRADE) predstavljaju najvišu razinu dokaza. Iako su sustavni pregledi pouzdaniji od drugih vrsta dokaza, sve razine hijerarhije dokaza ugrožene su sustavnim pogreškama (engl. bias); pogreškama dizajna studije (zloupotreba surogatnih ishoda, složenih ishoda itd.) i slučajnim pogreškama (igra slučaja). Kliničke istraživačke infrastrukture mogu pomoći u pružanju većih i adekvatnije provedenih ispitivanja. Sekvencijska analiza studija može pomoći pri odlučivanju kada postoji dovoljna razina dokaza u metaanalizama. Ako se prijetnje valjanosti kliničkih istraživanja pažljivo razmatraju i minimiziraju, rezultati istraživanja bit će vrjedniji i korisniji pacientima i zdravstvenim sustavima