Comment on Bar-Sela et al. Cannabis Consumption Used by Cancer Patients During Immunotherapy Correlates with Poor Clinical Outcome. Cancers 2020, 12 , 2447.

Simple Summary: Medical cannabis is an evidence-based treatment for chronic pain and chemotherapy-induced nausea and vomiting. Immunotherapies like pembrolizumab work by blocking proteins that stop the immune system from working properly. This commentary critically analyzes a small study by Bar-Sela...

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Publicado en:Cancers Vol. 17; no. 17; pp. 2754 - 2776
Autores principales: Piper, Brian J., Dobbins, Duncan X., Graham, Jason, Churilla, Thomas M., Bordonaro, Michael
Formato: commentary equations & formulas pictorial tables/charts Journal Article
Publicado: MDPI Sep2025
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Sep2025
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      pub: MDPI
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        atl: Comment on Bar-Sela et al. Cannabis Consumption Used by Cancer Patients During Immunotherapy Correlates with Poor Clinical Outcome. Cancers 2020, 12 , 2447.
      aug:
        au:
          Piper, Brian J.
          Dobbins, Duncan X.
          Graham, Jason
          Churilla, Thomas M.
          Bordonaro, Michael
        affil: Department of Medical Education, Geisinger College of Health Sciences, Scranton, PA 18509, USA
      sug:
        subj:
          Cancer Patients
          Immune Checkpoint Inhibitors Pharmacodynamics
          Cannabis Pharmacodynamics
          Drug Interactions
          Treatment Outcomes
      ab: Simple Summary: Medical cannabis is an evidence-based treatment for chronic pain and chemotherapy-induced nausea and vomiting. Immunotherapies like pembrolizumab work by blocking proteins that stop the immune system from working properly. This commentary critically analyzes a small study by Bar-Sela and coworkers, which appeared to show that cannabis made immunotherapies work less well in patients. Scientific papers should describe what they did in the Methods section and then carefully adhere to this in the Results section. However, we found many instances where there were disagreements between the Methods and Results sections in Bar-Sela's report. It is also riddled with errors in arithmetic, including unconventional rounding. The prior study did not consider the role of tobacco smoking, which may have been more important than cannabis use in their findings. We propose that artificial intelligence could be used by journals to identify mathematical and statistical errors and prevent studies that are not trustworthy from being published. The small (N = 102) prospective study by Bar-Sela and colleagues at Emek Medical Center in Israel) regarding diminished efficacy of immunotherapy in the setting of cannabis use would be an important discovery which could theoretically benefit the outcomes of oncology patients if verified by independent research teams, including by basic scientists. However, if this finding was spurious, clinical practice guidelines could recommend that oncology patients receiving immunotherapies be erroneously denied an evidence-based treatment for pain and chemotherapy-induced nausea and vomiting. Our full-length manuscript identified dozens of instances of unverifiable statistical information and even errors in arithmetic in this report. More briefly, our concerns regarding this well-cited (123 times) paper are as follows: (1) non-verifiable non-parametric statistics, including some that would change the statistical inferences; (2) difficulties with determining percentages; (3) switching from two-tailed tests in the Methods to one-tailed in the Results; (4) engaging in the unusual practice of floor rounding but not reporting this in the Methods; and (5) not reporting smoking, which could be a key confound. These concerns are serious errors that undermine the validity of the results and invalidate the conclusions that can be drawn from this prospective study about cannabis and immunotherapy.
      pubtype: Academic Journal
      doctype:
        commentary
        equations & formulas
        pictorial
        tables/charts
        Journal Article
      ougenre: Unknown
    language: English
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