Translating evidence into practice: eligibility criteria fail to eliminate clinically significant differences between real-world and study populations
Abstract Randomized controlled trials (RCTs) are regarded as the most reputable source of evidence. In some studies, factors beyond the intervention itself may contribute to the measured effect, an occurrence known as heterogeneity of treatment effect (HTE). If the RCT population differs from the re...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2020-05-01
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| Series: | npj Digital Medicine |
| Online Access: | https://doi.org/10.1038/s41746-020-0277-8 |
| _version_ | 1797642267893170176 |
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| author | Amelia J. Averitt Chunhua Weng Patrick Ryan Adler Perotte |
| author_facet | Amelia J. Averitt Chunhua Weng Patrick Ryan Adler Perotte |
| author_sort | Amelia J. Averitt |
| collection | DOAJ |
| description | Abstract Randomized controlled trials (RCTs) are regarded as the most reputable source of evidence. In some studies, factors beyond the intervention itself may contribute to the measured effect, an occurrence known as heterogeneity of treatment effect (HTE). If the RCT population differs from the real-world population on factors that induce HTE, the trials effect will not replicate. The RCTs eligibility criteria should identify the sub-population in which its evidence will replicate. However, the extent to which the eligibility criteria identify the appropriate population is unknown, which raises concerns for generalizability. We compared reported data from RCTs with real-world data from the electronic health records of a large, academic medical center that was curated according to RCT eligibility criteria. Our results show fundamental differences between the RCT population and our observational cohorts, which suggests that eligibility criteria may be insufficient for identifying the applicable real-world population in which RCT evidence will replicate. |
| first_indexed | 2024-03-11T13:57:40Z |
| format | Article |
| id | doaj.art-f2941ae407db4ad197e6d29fe2663bf3 |
| institution | Directory Open Access Journal |
| issn | 2398-6352 |
| language | English |
| last_indexed | 2024-03-11T13:57:40Z |
| publishDate | 2020-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Digital Medicine |
| spelling | doaj.art-f2941ae407db4ad197e6d29fe2663bf32023-11-02T05:59:28ZengNature Portfolionpj Digital Medicine2398-63522020-05-013111010.1038/s41746-020-0277-8Translating evidence into practice: eligibility criteria fail to eliminate clinically significant differences between real-world and study populationsAmelia J. Averitt0Chunhua Weng1Patrick Ryan2Adler Perotte3Department of Biomedical Informatics, Columbia UniversityDepartment of Biomedical Informatics, Columbia UniversityDepartment of Biomedical Informatics, Columbia UniversityDepartment of Biomedical Informatics, Columbia UniversityAbstract Randomized controlled trials (RCTs) are regarded as the most reputable source of evidence. In some studies, factors beyond the intervention itself may contribute to the measured effect, an occurrence known as heterogeneity of treatment effect (HTE). If the RCT population differs from the real-world population on factors that induce HTE, the trials effect will not replicate. The RCTs eligibility criteria should identify the sub-population in which its evidence will replicate. However, the extent to which the eligibility criteria identify the appropriate population is unknown, which raises concerns for generalizability. We compared reported data from RCTs with real-world data from the electronic health records of a large, academic medical center that was curated according to RCT eligibility criteria. Our results show fundamental differences between the RCT population and our observational cohorts, which suggests that eligibility criteria may be insufficient for identifying the applicable real-world population in which RCT evidence will replicate.https://doi.org/10.1038/s41746-020-0277-8 |
| spellingShingle | Amelia J. Averitt Chunhua Weng Patrick Ryan Adler Perotte Translating evidence into practice: eligibility criteria fail to eliminate clinically significant differences between real-world and study populations npj Digital Medicine |
| title | Translating evidence into practice: eligibility criteria fail to eliminate clinically significant differences between real-world and study populations |
| title_full | Translating evidence into practice: eligibility criteria fail to eliminate clinically significant differences between real-world and study populations |
| title_fullStr | Translating evidence into practice: eligibility criteria fail to eliminate clinically significant differences between real-world and study populations |
| title_full_unstemmed | Translating evidence into practice: eligibility criteria fail to eliminate clinically significant differences between real-world and study populations |
| title_short | Translating evidence into practice: eligibility criteria fail to eliminate clinically significant differences between real-world and study populations |
| title_sort | translating evidence into practice eligibility criteria fail to eliminate clinically significant differences between real world and study populations |
| url | https://doi.org/10.1038/s41746-020-0277-8 |
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