Calculating the individual probability of successful ocriplasmin treatment in eyes with vitreomacular traction–Validation and refinement of a multivariable prediction model
To evaluate a multivariable model predicting the individual probability of successful intravitreal ocriplasmin (IVO) treatment in eyes with vitreomacular traction (VMT). Data from three prospective, multicenter IVO studies (OASIS, ORBIT, and INJECT) were pooled. Patients were included if they were t...
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| Veröffentlicht in: | PloS one 2022-07, Vol.17 (7), p.e0270120-e0270120 |
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| creator | Paul, Christoph Müller, Hans-Helge Raber, Thomas Bertelmann, Thomas |
| description | To evaluate a multivariable model predicting the individual probability of successful intravitreal ocriplasmin (IVO) treatment in eyes with vitreomacular traction (VMT). Data from three prospective, multicenter IVO studies (OASIS, ORBIT, and INJECT) were pooled. Patients were included if they were treated for a symptomatic VMT without a full-thickness macular hole. A prediction model for VMT resolution using the factors 'age' and 'horizontal VMT diameter' was validated by receiver operating characteristic analysis and according to grouped prediction after calibration. Multivariable regression analysis was performed to check robustness and explore further improvements. Data from 591 eyes was included. In the univariate analysis all key factors (age, gender, VMT diameter, lens status, ERM) significantly correlated to treatment success. The prediction model was robust and clinically applicable to estimate the success rate of IVO treatment (AUC of ROC: 0.70). A refinement of the model was achieved through a calibration process. The developed multivariable model using 'horizontal VMT diameter' and 'age' is a valid tool for prediction of VMT resolution upon IVO treatment. |
| doi_str_mv | 10.1371/journal.pone.0270120 |
| format | Article |
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Data from three prospective, multicenter IVO studies (OASIS, ORBIT, and INJECT) were pooled. Patients were included if they were treated for a symptomatic VMT without a full-thickness macular hole. A prediction model for VMT resolution using the factors 'age' and 'horizontal VMT diameter' was validated by receiver operating characteristic analysis and according to grouped prediction after calibration. Multivariable regression analysis was performed to check robustness and explore further improvements. Data from 591 eyes was included. In the univariate analysis all key factors (age, gender, VMT diameter, lens status, ERM) significantly correlated to treatment success. The prediction model was robust and clinically applicable to estimate the success rate of IVO treatment (AUC of ROC: 0.70). A refinement of the model was achieved through a calibration process. The developed multivariable model using 'horizontal VMT diameter' and 'age' is a valid tool for prediction of VMT resolution upon IVO treatment.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0270120</identifier><identifier>PMID: 35877658</identifier><language>eng</language><publisher>San Francisco: Public Library of Science</publisher><subject>Age ; Biology and Life Sciences ; Calibration ; Complications and side effects ; Datasets ; Diameters ; Gender ; Medicine and Health Sciences ; Modelling ; Observational studies ; Ocriplasmin ; Patient outcomes ; Patients ; Physical Sciences ; Prediction models ; Predictions ; Probability ; Regression analysis ; Research and Analysis Methods ; Robustness (mathematics) ; Statistical analysis ; Success ; Traction</subject><ispartof>PloS one, 2022-07, Vol.17 (7), p.e0270120-e0270120</ispartof><rights>COPYRIGHT 2022 Public Library of Science</rights><rights>2022 Paul et al. 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Data from three prospective, multicenter IVO studies (OASIS, ORBIT, and INJECT) were pooled. Patients were included if they were treated for a symptomatic VMT without a full-thickness macular hole. A prediction model for VMT resolution using the factors 'age' and 'horizontal VMT diameter' was validated by receiver operating characteristic analysis and according to grouped prediction after calibration. Multivariable regression analysis was performed to check robustness and explore further improvements. Data from 591 eyes was included. In the univariate analysis all key factors (age, gender, VMT diameter, lens status, ERM) significantly correlated to treatment success. The prediction model was robust and clinically applicable to estimate the success rate of IVO treatment (AUC of ROC: 0.70). A refinement of the model was achieved through a calibration process. The developed multivariable model using 'horizontal VMT diameter' and 'age' is a valid tool for prediction of VMT resolution upon IVO treatment.</description><subject>Age</subject><subject>Biology and Life Sciences</subject><subject>Calibration</subject><subject>Complications and side effects</subject><subject>Datasets</subject><subject>Diameters</subject><subject>Gender</subject><subject>Medicine and Health Sciences</subject><subject>Modelling</subject><subject>Observational studies</subject><subject>Ocriplasmin</subject><subject>Patient outcomes</subject><subject>Patients</subject><subject>Physical Sciences</subject><subject>Prediction models</subject><subject>Predictions</subject><subject>Probability</subject><subject>Regression analysis</subject><subject>Research and Analysis Methods</subject><subject>Robustness (mathematics)</subject><subject>Statistical 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Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Paul, Christoph</au><au>Müller, Hans-Helge</au><au>Raber, Thomas</au><au>Bertelmann, Thomas</au><au>Wang, I-Jong</au><aucorp>on behalf of the EXPORT study group</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Calculating the individual probability of successful ocriplasmin treatment in eyes with vitreomacular traction–Validation and refinement of a multivariable prediction model</atitle><jtitle>PloS one</jtitle><date>2022-07-25</date><risdate>2022</risdate><volume>17</volume><issue>7</issue><spage>e0270120</spage><epage>e0270120</epage><pages>e0270120-e0270120</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>To evaluate a multivariable model predicting the individual probability of successful intravitreal ocriplasmin (IVO) treatment in eyes with vitreomacular traction (VMT). Data from three prospective, multicenter IVO studies (OASIS, ORBIT, and INJECT) were pooled. Patients were included if they were treated for a symptomatic VMT without a full-thickness macular hole. A prediction model for VMT resolution using the factors 'age' and 'horizontal VMT diameter' was validated by receiver operating characteristic analysis and according to grouped prediction after calibration. Multivariable regression analysis was performed to check robustness and explore further improvements. Data from 591 eyes was included. In the univariate analysis all key factors (age, gender, VMT diameter, lens status, ERM) significantly correlated to treatment success. The prediction model was robust and clinically applicable to estimate the success rate of IVO treatment (AUC of ROC: 0.70). A refinement of the model was achieved through a calibration process. The developed multivariable model using 'horizontal VMT diameter' and 'age' is a valid tool for prediction of VMT resolution upon IVO treatment.</abstract><cop>San Francisco</cop><pub>Public Library of Science</pub><pmid>35877658</pmid><doi>10.1371/journal.pone.0270120</doi><tpages>e0270120</tpages><orcidid>https://orcid.org/0000-0002-6458-0302</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Age Biology and Life Sciences Calibration Complications and side effects Datasets Diameters Gender Medicine and Health Sciences Modelling Observational studies Ocriplasmin Patient outcomes Patients Physical Sciences Prediction models Predictions Probability Regression analysis Research and Analysis Methods Robustness (mathematics) Statistical analysis Success Traction |
| title | Calculating the individual probability of successful ocriplasmin treatment in eyes with vitreomacular traction–Validation and refinement of a multivariable prediction model |
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