Drug effectiveness for COVID-19 inpatients inferred from Japanese medical claim data using propensity score matching [version 1; peer review: 1 approved with reservations]

Background: Earlier studies and clinical trials have shown that the drugs such as antiviral drugs, antibody cocktails, and steroids and anti-inflammatory drugs are expected to prevent severe coronavirus 2019 (COVID-19) outcomes and death. Methods: We used observational data for Japan to assess the e...

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Published inF1000 research Vol. 12; p. 398
Main Authors Mitsushima, Shingo, Horiguchi, Hiromasa, Taniguchi, Kiyosu
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LanguageEnglish
Published London, UK F1000 Research Limited 2023
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Abstract Background: Earlier studies and clinical trials have shown that the drugs such as antiviral drugs, antibody cocktails, and steroids and anti-inflammatory drugs are expected to prevent severe coronavirus 2019 (COVID-19) outcomes and death. Methods: We used observational data for Japan to assess the effectiveness of these drugs for COVID-19. We applied propensity scoring, which can treat the choice of administered drug as a random assignment to inpatients, to the Medical Information Analysis Databank operated by National Hospital Organization in Japan. The outcome was defined as mortality. Subjects were all inpatients, inpatients with oxygen administration, and inpatients using respiratory ventilators, classified by three age classes: all ages, 65 years old or older, and younger than 65 years old. Information about demographical characteristics, underlying disease, administered drug, the proportion of Alpha, Beta and Omicron variant strains, and vaccine coverage were used as explanatory variable in logistic regression. Results: Estimated results indicated that only an antibody cocktail (sotrovimab, casirivimab and imdevimab) raised the probability to save life consistently. By contrast, other drugs might reduce the probability of saving life. The results indicated that an antiviral drug (remdesivir), a steroid (dexamethasone), and an anti-inflammatory drug (baricitinib and tocilizumab) might not contribute to saving life even at the pseudo-situation of random assignment. However, this logistic regression at the first step might have only insufficient explanatory power. Conclusions: We found a high likelihood that antibody cocktails were consistently effective to raise the probability of saving life, though a lesser likelihood in other drugs for older patients with mild to severe severity and all age patients with moderate severity.
AbstractList Background: Earlier studies and clinical trials have shown that the drugs such as antiviral drugs, antibody cocktails, and steroids and anti-inflammatory drugs are expected to prevent severe coronavirus 2019 (COVID-19) outcomes and death. Methods: We used observational data for Japan to assess the effectiveness of these drugs for COVID-19. We applied propensity scoring, which can treat the choice of administered drug as a random assignment to inpatients, to the Medical Information Analysis Databank operated by National Hospital Organization in Japan. The outcome was defined as mortality. Subjects were all inpatients, inpatients with oxygen administration, and inpatients using respiratory ventilators, classified by three age classes: all ages, 65 years old or older, and younger than 65 years old. Information about demographical characteristics, underlying disease, administered drug, the proportion of Alpha, Beta and Omicron variant strains, and vaccine coverage were used as explanatory variable in logistic regression. Results: Estimated results indicated that only an antibody cocktail (sotrovimab, casirivimab and imdevimab) raised the probability to save life consistently. By contrast, other drugs might reduce the probability of saving life. The results indicated that an antiviral drug (remdesivir), a steroid (dexamethasone), and an anti-inflammatory drug (baricitinib and tocilizumab) might not contribute to saving life even at the pseudo-situation of random assignment. However, this logistic regression at the first step might have only insufficient explanatory power. Conclusions: We found a high likelihood that antibody cocktails were consistently effective to raise the probability of saving life, though a lesser likelihood in other drugs for older patients with mild to severe severity and all age patients with moderate severity.
Background: Earlier studies and clinical trials have shown that the drugs such as antiviral drugs, antibody cocktails, and steroids and anti-inflammatory drugs are expected to prevent severe coronavirus 2019 (COVID-19) outcomes and death. Methods: We used observational data for Japan to assess the effectiveness of these drugs for COVID-19. We applied propensity scoring, which can treat the choice of administered drug as a random assignment to inpatients, to the Medical Information Analysis Databank operated by National Hospital Organization in Japan. The outcome was defined as mortality. Subjects were all inpatients, inpatients with oxygen administration, and inpatients using respiratory ventilators, classified by three age classes: all ages, 65 years old or older, and younger than 65 years old. Information about demographical characteristics, underlying disease, administered drug, the proportion of Alpha, Beta and Omicron variant strains, and vaccine coverage were used as explanatory variable in logistic regression. Results: Estimated results indicated that only an antibody cocktail (sotrovimab, casirivimab and imdevimab) raised the probability to save life consistently. By contrast, other drugs might reduce the probability of saving life. The results indicated that an antiviral drug (remdesivir), a steroid (dexamethasone), and an anti-inflammatory drug (baricitinib and tocilizumab) might not contribute to saving life even at the pseudo-situation of random assignment. However, this logistic regression at the first step might have only insufficient explanatory power. Conclusions: We found a high likelihood that antibody cocktails were consistently effective to raise the probability of saving life, though a lesser likelihood in other drugs for older patients with mild to severe severity and all age patients with moderate severity.
Author Taniguchi, Kiyosu
Horiguchi, Hiromasa
Mitsushima, Shingo
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Keywords COVID-19
antiviral drug
mutated strain
mortality
underlying diseases
antibody cocktail
steroid and anti-inflammatory drug
Language English
License http://creativecommons.org/licenses/by/4.0/: This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Notes No competing interests were disclosed.
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Title Drug effectiveness for COVID-19 inpatients inferred from Japanese medical claim data using propensity score matching [version 1; peer review: 1 approved with reservations]
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