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Accuracy of algorithms to identify patients with a diagnosis of major cancers and cancer-related adverse events in an administrative database: a validation study in an acute care hospital in Japan
OBJECTIVES: Validation studies in oncology are limited in Japan. This study was conducted to evaluate the accuracy of diagnosis and adverse event (AE) definitions for specific cancers in a Japanese health administrative real-world database (RWD). DESIGN AND SETTING: Retrospective observational valid...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BMJ Publishing Group
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9280899/ https://www.ncbi.nlm.nih.gov/pubmed/35831049 http://dx.doi.org/10.1136/bmjopen-2021-055459 |
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author | Fujiwara, Takashi Kanemitsu, Takashi Tajima, Kosei Yuri, Akinori Iwasaku, Masahiro Okumura, Yasuyuki Tokumasu, Hironobu |
author_facet | Fujiwara, Takashi Kanemitsu, Takashi Tajima, Kosei Yuri, Akinori Iwasaku, Masahiro Okumura, Yasuyuki Tokumasu, Hironobu |
author_sort | Fujiwara, Takashi |
collection | PubMed |
description | OBJECTIVES: Validation studies in oncology are limited in Japan. This study was conducted to evaluate the accuracy of diagnosis and adverse event (AE) definitions for specific cancers in a Japanese health administrative real-world database (RWD). DESIGN AND SETTING: Retrospective observational validation study to assess the diagnostic accuracy of electronic medical records (EMRs) and claim coding regarding oncology diagnosis and AEs based on medical record review in the RWD. The sensitivity and positive predictive value (PPV) with 95% CIs were calculated. PARTICIPANTS: The validation cohort included patients with lung (n=2257), breast (n=1121), colorectal (n=1773), ovarian (n=216) and bladder (n=575) cancer who visited the hospital between January 2014 and December 2018, and those with prostate cancer (n=3491) visiting between January 2009 and December 2018, who were identified using EMRs. OUTCOMES: Key outcomes included primary diagnosis, deaths and AEs. RESULTS: For primary diagnosis, sensitivity and PPV for the respective cancers were as follows: lung, 100.0% (96.6 to 100.0) and 81.0% (74.9 to 86.2); breast, 100.0% (96.3 to 100.0) and 74.0% (67.3 to 79.9); colorectal, 100.0% (96.6 to 100.0) and 80.5% (74.3 to 85.8); ovarian, 89.8% (77.8 to 96.6) and 75.9% (62.8 to 86.1); bladder, 78.6% (63.2 to 89.7) and 67.3% (52.5 to 0.1); prostate, 100.0% (93.2 to 100.0) and 79.0% (69.7 to 86.5). Sensitivity and PPV for death were as follows: lung, 97.0% (84.2 to 99.9) and 100.0% (84.2 to 100.0); breast, 100.0% (1.3 to 100.0) and 100.0% (1.3 to 100.0); colorectal, 100.0% (28.4 to 100.0) and 100.0% (28.4 to 100.0); ovarian, 100.0% (35.9 to 100.0) and 100.0% (35.9 to 100.0); bladder, 100.0% (9.4–100.0) and 100.0% (9.4 to 100.0); prostate, 75.0% (19.4 to 99.4) and 100.0% (19.4 to 100.0). Overall, PPV tended to be low, with the definition based on International Classification of Diseases, 10th revision alone for AEs. CONCLUSION: Diagnostic accuracy was not so high, and therefore needs to be further investigated. TRIAL REGISTRATION NUMBER: University Hospital Medical Information Network (UMIN) Clinical Trials Registry (UMIN000039345). |
format | Online Article Text |
id | pubmed-9280899 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-92808992022-07-28 Accuracy of algorithms to identify patients with a diagnosis of major cancers and cancer-related adverse events in an administrative database: a validation study in an acute care hospital in Japan Fujiwara, Takashi Kanemitsu, Takashi Tajima, Kosei Yuri, Akinori Iwasaku, Masahiro Okumura, Yasuyuki Tokumasu, Hironobu BMJ Open Oncology OBJECTIVES: Validation studies in oncology are limited in Japan. This study was conducted to evaluate the accuracy of diagnosis and adverse event (AE) definitions for specific cancers in a Japanese health administrative real-world database (RWD). DESIGN AND SETTING: Retrospective observational validation study to assess the diagnostic accuracy of electronic medical records (EMRs) and claim coding regarding oncology diagnosis and AEs based on medical record review in the RWD. The sensitivity and positive predictive value (PPV) with 95% CIs were calculated. PARTICIPANTS: The validation cohort included patients with lung (n=2257), breast (n=1121), colorectal (n=1773), ovarian (n=216) and bladder (n=575) cancer who visited the hospital between January 2014 and December 2018, and those with prostate cancer (n=3491) visiting between January 2009 and December 2018, who were identified using EMRs. OUTCOMES: Key outcomes included primary diagnosis, deaths and AEs. RESULTS: For primary diagnosis, sensitivity and PPV for the respective cancers were as follows: lung, 100.0% (96.6 to 100.0) and 81.0% (74.9 to 86.2); breast, 100.0% (96.3 to 100.0) and 74.0% (67.3 to 79.9); colorectal, 100.0% (96.6 to 100.0) and 80.5% (74.3 to 85.8); ovarian, 89.8% (77.8 to 96.6) and 75.9% (62.8 to 86.1); bladder, 78.6% (63.2 to 89.7) and 67.3% (52.5 to 0.1); prostate, 100.0% (93.2 to 100.0) and 79.0% (69.7 to 86.5). Sensitivity and PPV for death were as follows: lung, 97.0% (84.2 to 99.9) and 100.0% (84.2 to 100.0); breast, 100.0% (1.3 to 100.0) and 100.0% (1.3 to 100.0); colorectal, 100.0% (28.4 to 100.0) and 100.0% (28.4 to 100.0); ovarian, 100.0% (35.9 to 100.0) and 100.0% (35.9 to 100.0); bladder, 100.0% (9.4–100.0) and 100.0% (9.4 to 100.0); prostate, 75.0% (19.4 to 99.4) and 100.0% (19.4 to 100.0). Overall, PPV tended to be low, with the definition based on International Classification of Diseases, 10th revision alone for AEs. CONCLUSION: Diagnostic accuracy was not so high, and therefore needs to be further investigated. TRIAL REGISTRATION NUMBER: University Hospital Medical Information Network (UMIN) Clinical Trials Registry (UMIN000039345). BMJ Publishing Group 2022-07-13 /pmc/articles/PMC9280899/ /pubmed/35831049 http://dx.doi.org/10.1136/bmjopen-2021-055459 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Oncology Fujiwara, Takashi Kanemitsu, Takashi Tajima, Kosei Yuri, Akinori Iwasaku, Masahiro Okumura, Yasuyuki Tokumasu, Hironobu Accuracy of algorithms to identify patients with a diagnosis of major cancers and cancer-related adverse events in an administrative database: a validation study in an acute care hospital in Japan |
title | Accuracy of algorithms to identify patients with a diagnosis of major cancers and cancer-related adverse events in an administrative database: a validation study in an acute care hospital in Japan |
title_full | Accuracy of algorithms to identify patients with a diagnosis of major cancers and cancer-related adverse events in an administrative database: a validation study in an acute care hospital in Japan |
title_fullStr | Accuracy of algorithms to identify patients with a diagnosis of major cancers and cancer-related adverse events in an administrative database: a validation study in an acute care hospital in Japan |
title_full_unstemmed | Accuracy of algorithms to identify patients with a diagnosis of major cancers and cancer-related adverse events in an administrative database: a validation study in an acute care hospital in Japan |
title_short | Accuracy of algorithms to identify patients with a diagnosis of major cancers and cancer-related adverse events in an administrative database: a validation study in an acute care hospital in Japan |
title_sort | accuracy of algorithms to identify patients with a diagnosis of major cancers and cancer-related adverse events in an administrative database: a validation study in an acute care hospital in japan |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9280899/ https://www.ncbi.nlm.nih.gov/pubmed/35831049 http://dx.doi.org/10.1136/bmjopen-2021-055459 |
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