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  1. Article ; Online: CORR Insights®: Does Artificial Intelligence Outperform Natural Intelligence in Interpretation of Musculoskeletal Radiological Studies? A Systematic Review.

    Porcher, Raphaël

    Clinical orthopaedics and related research

    2020  Volume 478, Issue 12, Page(s) 2765–2767

    MeSH term(s) Artificial Intelligence ; Humans ; Image Interpretation, Computer-Assisted ; Intelligence
    Language English
    Publishing date 2020-12-28
    Publishing country United States
    Document type Journal Article ; Comment
    ZDB-ID 80301-7
    ISSN 1528-1132 ; 0009-921X
    ISSN (online) 1528-1132
    ISSN 0009-921X
    DOI 10.1097/CORR.0000000000001415
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: What should be done and what should be avoided when comparing two treatments?

    Brion Bouvier, Florie / Porcher, Raphaël

    Best practice & research. Clinical haematology

    2023  Volume 36, Issue 2, Page(s) 101473

    Abstract: The preferred approach to compare two treatments is a randomized controlled trial (RCT). Indeed, randomization ensures that the groups compared are similar. Well-designed and well-conducted RCTs thus allow to draw causal conclusions on the relative ... ...

    Abstract The preferred approach to compare two treatments is a randomized controlled trial (RCT). Indeed, randomization ensures that the groups compared are similar. Well-designed and well-conducted RCTs thus allow to draw causal conclusions on the relative efficacy and safety of treatments compared. However, it is not always possible to conduct RCTs for all clinical questions of interest, and observational data may also be used to infer on the relative effectiveness of treatments. In this review, we present different approaches that allow statistically valid comparisons of the effectiveness of treatments using observational data under some assumptions. Those are based on regression modelling or the propensity score. We also present the principles of target trial emulation.
    MeSH term(s) Humans ; Randomized Controlled Trials as Topic
    Language English
    Publishing date 2023-05-06
    Publishing country Netherlands
    Document type Journal Article ; Review ; Research Support, Non-U.S. Gov't
    ZDB-ID 2048027-1
    ISSN 1532-1924 ; 1521-6926
    ISSN (online) 1532-1924
    ISSN 1521-6926
    DOI 10.1016/j.beha.2023.101473
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: CORR Insights

    Porcher, Raphaël

    Clinical orthopaedics and related research

    2017  Volume 475, Issue 9, Page(s) 2271–2273

    MeSH term(s) Bone Neoplasms ; Humans ; Musculoskeletal System ; ROC Curve
    Language English
    Publishing date 2017-06-27
    Publishing country United States
    Document type Journal Article ; Comment
    ZDB-ID 80301-7
    ISSN 1528-1132 ; 0009-921X
    ISSN (online) 1528-1132
    ISSN 0009-921X
    DOI 10.1007/s11999-017-5434-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: CORR Insights

    Porcher, Raphaël

    Clinical orthopaedics and related research

    2017  Volume 475, Issue 3, Page(s) 881–883

    MeSH term(s) Bayes Theorem ; Humans ; Lumbar Vertebrae/surgery ; Lumbosacral Region ; Spinal Fusion ; Spinal Stenosis/surgery ; Treatment Outcome
    Language English
    Publishing date 2017
    Publishing country United States
    Document type Journal Article ; Comment
    ZDB-ID 80301-7
    ISSN 1528-1132 ; 0009-921X
    ISSN (online) 1528-1132
    ISSN 0009-921X
    DOI 10.1007/s11999-016-5225-1
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: The COVID-19 and chloroquine infodemic: Cross-sectional observational study of content analysis on YouTube.

    Poncelet, Cynthia / Porcher, Raphaël / Nguyen, Yên-Lan

    PloS one

    2023  Volume 18, Issue 9, Page(s) e0286964

    Abstract: The objective of this study is to evaluate the association between quality and features related to internet users of the most viewed YouTube videos about COVID-19 and chloroquine, during the first wave of the pandemic. We conducted a cross-sectional ... ...

    Abstract The objective of this study is to evaluate the association between quality and features related to internet users of the most viewed YouTube videos about COVID-19 and chloroquine, during the first wave of the pandemic. We conducted a cross-sectional observational study focusing on the most viewed YouTube videos on COVID-19 and chloroquine treatment, in French and English. The primary outcome was the association between video quality as assessed by DISCERN and modified JAMA scores, and video features related to internet users as assessed by number of viewership and likes. By June 2020, 168 videos accumulating more than 57 million views and nearly 2 million reactions from Internet users, were included. Most of the videos did not support or oppose the treatment and came from news channels (N = 100; 60%). Videos taking sides were mostly pro-chloroquine (N = 69; 89%). The number of non-factual videos analyzed was very low (N = 3; 2%). The quality of the videos was average (mean DISCERN score = 2.4 (DS 1.0) and mean modified JAMA score = 2.6 (DS 0.6)) and declined over time. The best quality videos were those published by health care professionals or those from educational channels. Most experts interviewed were men (N = 136; 81%). More than 1 in 5 videos featured a political figure (N = 35; 21%), and these were mostly pro-chloroquine with lower DISCERN or modified JAMA scores (p<0.001). We found an association between the number of likes and the quality of the videos evaluated by the DISCERN score (rho = 0.29; p<0.001) and the modified JAMA score (rho = 0.30; p<0.001). The association observed between the quality of the videos and the number of likes suggests a better health literacy and critical thinking of lay internet users. Although YouTube has become a major player in the dissemination of medical information, more involvement of health professionals and governmental organizations is needed.
    MeSH term(s) Male ; Humans ; Female ; COVID-19/epidemiology ; COVID-19 Drug Treatment ; Cross-Sectional Studies ; Infodemic ; Social Media ; Chloroquine/therapeutic use ; Information Dissemination ; Video Recording ; Reproducibility of Results
    Chemical Substances Chloroquine (886U3H6UFF)
    Language English
    Publishing date 2023-09-28
    Publishing country United States
    Document type Observational Study ; Journal Article
    ZDB-ID 2267670-3
    ISSN 1932-6203 ; 1932-6203
    ISSN (online) 1932-6203
    ISSN 1932-6203
    DOI 10.1371/journal.pone.0286964
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Reply to Binghao Zhao, Ruidong Zhang, and Jiaming Wu's Letter to the Editor re: Ana Cavillon, Damien Pouessel, Nadine Houédé, et al. Assessing Long-term Treatment Benefits Using Complementary Statistical Approaches: An In Silico Analysis of the Phase III Keynote-045 and Checkmate-214 Immune Checkpoint Inhibitor Trials. Eur Urol. In press. https://doi.org/10.1016/j.eururo.2023.02.011.

    Cavillon, Ana / Porcher, Raphael / Filleron, Thomas

    European urology

    2023  Volume 84, Issue 1, Page(s) e22–e23

    MeSH term(s) Humans ; Immune Checkpoint Inhibitors
    Chemical Substances Immune Checkpoint Inhibitors
    Language English
    Publishing date 2023-04-27
    Publishing country Switzerland
    Document type Letter ; Comment
    ZDB-ID 193790-x
    ISSN 1873-7560 ; 1421-993X ; 0302-2838
    ISSN (online) 1873-7560 ; 1421-993X
    ISSN 0302-2838
    DOI 10.1016/j.eururo.2023.04.016
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Editorial: What Readers and Clinician Scientists Need to Know About the "Other" EQUATOR.

    Leopold, Seth S / Porcher, Raphaël

    Clinical orthopaedics and related research

    2021  Volume 479, Issue 4, Page(s) 643–647

    MeSH term(s) Abbreviations as Topic ; Animals ; Biomedical Research/standards ; Checklist/standards ; Cooperative Behavior ; Guideline Adherence/standards ; Humans ; Interdisciplinary Communication ; International Cooperation ; Orthopedics/standards ; Practice Guidelines as Topic/standards ; Research Design
    Language English
    Publishing date 2021-03-02
    Publishing country United States
    Document type Editorial
    ZDB-ID 80301-7
    ISSN 1528-1132 ; 0009-921X
    ISSN (online) 1528-1132
    ISSN 0009-921X
    DOI 10.1097/CORR.0000000000001708
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Do machine learning methods lead to similar individualized treatment rules? A comparison study on real data.

    Bouvier, Florie / Peyrot, Etienne / Balendran, Alan / Ségalas, Corentin / Roberts, Ian / Petit, François / Porcher, Raphaël

    Statistics in medicine

    2024  

    Abstract: Identifying patients who benefit from a treatment is a key aspect of personalized medicine, which allows the development of individualized treatment rules (ITRs). Many machine learning methods have been proposed to create such rules. However, to what ... ...

    Abstract Identifying patients who benefit from a treatment is a key aspect of personalized medicine, which allows the development of individualized treatment rules (ITRs). Many machine learning methods have been proposed to create such rules. However, to what extent the methods lead to similar ITRs, that is, recommending the same treatment for the same individuals is unclear. In this work, we compared 22 of the most common approaches in two randomized control trials. Two classes of methods can be distinguished. The first class of methods relies on predicting individualized treatment effects from which an ITR is derived by recommending the treatment evaluated to the individuals with a predicted benefit. In the second class, methods directly estimate the ITR without estimating individualized treatment effects. For each trial, the performance of ITRs was assessed by various metrics, and the pairwise agreement between all ITRs was also calculated. Results showed that the ITRs obtained via the different methods generally had considerable disagreements regarding the patients to be treated. A better concordance was found among akin methods. Overall, when evaluating the performance of ITRs in a validation sample, all methods produced ITRs with limited performance, suggesting a high potential for optimism. For non-parametric methods, this optimism was likely due to overfitting. The different methods do not lead to similar ITRs and are therefore not interchangeable. The choice of the method strongly influences for which patients a certain treatment is recommended, drawing some concerns about their practical use.
    Language English
    Publishing date 2024-03-12
    Publishing country England
    Document type Journal Article
    ZDB-ID 843037-8
    ISSN 1097-0258 ; 0277-6715
    ISSN (online) 1097-0258
    ISSN 0277-6715
    DOI 10.1002/sim.10059
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Estimating individualized treatment effects using an individual participant data meta-analysis.

    Bouvier, Florie / Chaimani, Anna / Peyrot, Etienne / Gueyffier, François / Grenet, Guillaume / Porcher, Raphaël

    BMC medical research methodology

    2024  Volume 24, Issue 1, Page(s) 74

    Abstract: Background: One key aspect of personalized medicine is to identify individuals who benefit from an intervention. Some approaches have been developed to estimate individualized treatment effects (ITE) with a single randomized control trial (RCT) or ... ...

    Abstract Background: One key aspect of personalized medicine is to identify individuals who benefit from an intervention. Some approaches have been developed to estimate individualized treatment effects (ITE) with a single randomized control trial (RCT) or observational data, but they are often underpowered for the ITE estimation. Using individual participant data meta-analyses (IPD-MA) might solve this problem. Few studies have investigated how to develop risk prediction models with IPD-MA, and it remains unclear how to combine those methods with approaches used for ITE estimation. In this article, we compared different approaches using both simulated and real data with binary and time-to-event outcomes to estimate the individualized treatment effects from an IPD-MA in a one-stage approach.
    Methods: We compared five one-stage models: naive model (NA), random intercept (RI), stratified intercept (SI), rank-1 (R1), and fully stratified (FS), built with two different strategies, the S-learner and the T-learner constructed with a Monte Carlo simulation study in which we explored different scenarios with a binary or a time-to-event outcome. To evaluate the performance of the models, we used the c-statistic for benefit, the calibration of predictions, and the mean squared error. The different models were also used on the INDANA IPD-MA, comparing an anti-hypertensive treatment to no treatment or placebo (
    Results: Simulation results showed that using the S-learner led to better ITE estimation performances for both binary and time-to-event outcomes. None of the risk models stand out and had significantly better results. For the INDANA dataset with a binary outcome, the naive and the random intercept models had the best performances.
    Conclusions: For the choice of the strategy, using interactions with treatment (the S-learner) is preferable. For the choice of the method, no approach is better than the other.
    MeSH term(s) Humans ; Models, Statistical ; Computer Simulation ; Randomized Controlled Trials as Topic
    Language English
    Publishing date 2024-03-25
    Publishing country England
    Document type Meta-Analysis ; Journal Article
    ZDB-ID 2041362-2
    ISSN 1471-2288 ; 1471-2288
    ISSN (online) 1471-2288
    ISSN 1471-2288
    DOI 10.1186/s12874-024-02202-9
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Authors' Reply: Kidney Histopathology in ANCA-Associated Vasculitides Treated with Plasma Exchange.

    Nezam, Dorian / Porcher, Raphaël / Grolleau, François / Terrier, Benjamin

    Journal of the American Society of Nephrology : JASN

    2022  Volume 33, Issue 6, Page(s) 1224–1225

    MeSH term(s) Anti-Neutrophil Cytoplasmic Antibody-Associated Vasculitis/therapy ; Antibodies, Antineutrophil Cytoplasmic ; Humans ; Kidney ; Plasma Exchange
    Chemical Substances Antibodies, Antineutrophil Cytoplasmic
    Language English
    Publishing date 2022-04-11
    Publishing country United States
    Document type Letter ; Comment
    ZDB-ID 1085942-1
    ISSN 1533-3450 ; 1046-6673
    ISSN (online) 1533-3450
    ISSN 1046-6673
    DOI 10.1681/ASN.2022030269
    Database MEDical Literature Analysis and Retrieval System OnLINE

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