{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,13]],"date-time":"2026-09-13T17:03:36Z","timestamp":1789319016101,"version":"build-2803163510"},"reference-count":36,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100020771","name":"Young Scientists Fund of the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["82300127 and 82600263"],"award-info":[{"award-number":["82300127 and 82600263"]}],"id":[{"id":"10.13039\/501100020771","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Project of Science and Technology Commission of Shanghai Municipality","award":["20Y11902500"],"award-info":[{"award-number":["20Y11902500"]}]},{"name":"Project of Science and Technology Commission of Shanghai Municipality","award":["21140903400"],"award-info":[{"award-number":["21140903400"]}]},{"name":"Shanghai Sailing Program","award":["21YF1442500"],"award-info":[{"award-number":["21YF1442500"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Ther Adv Respir Dis"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Neuromodulators (e.g., Gabapentin, Baclofen, and Flupentixol-melitracen) are widely prescribed for refractory chronic cough (RCC); however, heterogeneous treatment responses remain a significant challenge for optimal agent selection.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>This study aimed to develop an interpretable machine learning (ML) model to predict individual patient responses to these therapies.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design<\/jats:title>\n                    <jats:p>Single-center retrospective observational study.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This retrospective cohort study included 730 patients with RCC treated with neuromodulators from 2016 to 2023. We extracted comprehensive clinical data, including demographics, patient-reported outcomes, medication history, and laboratory findings. Six ML algorithms underwent rigorous hyperparameter tuning and 10-fold cross-validation. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration and decision curve analysis (DCA). The optimal model was interpreted using SHapley Additive exPlanations (SHAP).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The overall neuromodulator response rate was 56.8%. A 14-variable Random Forest (RF) model demonstrated the best performance, yielding a training AUC of 0.825 (95% CI: 0.785-0.865; calibration slope: 0.984) and a robust cross-validated AUC of 0.718 (95% CI: 0.655-0.765; calibration slope: 0.956). SHAP analysis demonstrated that pre-treatment cough severity, history of esophagitis, and specific gastroesophageal reflux-related symptoms scores were identified as the top predictive features associated with treatment outcomes. The free online clinical decision-support application was deployed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>We developed and internally validated an interpretable ML model capable of predicting neuromodulator efficacy in RCC. The integration of SHAP clarifies feature attributions to support individualized, data-driven treatment selection.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/17534666261487594","type":"journal-article","created":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T18:01:50Z","timestamp":1789063310000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Predicting response to neuromodulators in refractory chronic cough: An interpretable machine learning approach"],"prefix":"10.1177","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4980-8580","authenticated-orcid":false,"given":"Li","family":"Zhang","sequence":"first","affiliation":[{"name":"Tongji University School of Medicine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alimire","family":"Aierken","sequence":"additional","affiliation":[{"name":"Tongji University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiang","family":"Chen","sequence":"additional","affiliation":[{"name":"Tongji University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhongmin","family":"Qiu","sequence":"additional","affiliation":[{"name":"Tongji University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ran","family":"Dong","sequence":"additional","affiliation":[{"name":"Tongji University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,9,10]]},"reference":[{"key":"e_1_3_8_2_2","doi-asserted-by":"publisher","DOI":"10.1183\/09031936.00218714"},{"key":"e_1_3_8_3_2","doi-asserted-by":"publisher","DOI":"10.4168\/aair.2017.9.5.394"},{"key":"e_1_3_8_4_2","doi-asserted-by":"publisher","DOI":"10.1183\/16000617.0127-2021"},{"key":"e_1_3_8_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eclinm.2023.102100"},{"key":"e_1_3_8_6_2","doi-asserted-by":"publisher","DOI":"10.1177\/17534666231167716"},{"key":"e_1_3_8_7_2","doi-asserted-by":"publisher","DOI":"10.1111\/apt.15169"},{"key":"e_1_3_8_8_2","doi-asserted-by":"publisher","DOI":"10.21037\/jtd.2018.09.153"},{"key":"e_1_3_8_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eclinm.2025.103367"},{"key":"e_1_3_8_10_2","doi-asserted-by":"publisher","DOI":"10.1177\/2040622320982463"},{"key":"e_1_3_8_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.rmed.2021.106439"},{"key":"e_1_3_8_12_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12931-024-02793-3"},{"key":"e_1_3_8_13_2","doi-asserted-by":"publisher","DOI":"10.1080\/17476348.2020.1743181"},{"key":"e_1_3_8_14_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-018-0316-z"},{"key":"e_1_3_8_15_2","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbae688"},{"key":"e_1_3_8_16_2","doi-asserted-by":"publisher","DOI":"10.1002\/prca.70024"},{"key":"e_1_3_8_17_2","doi-asserted-by":"publisher","DOI":"10.7150\/ijms.58191"},{"key":"e_1_3_8_18_2","volume-title":"A Unifed Approach to Interpreting Model Predictions","author":"Lundberg S","year":"2017","unstructured":"Lundberg S, Lee SI. A Unifed Approach to Interpreting Model Predictions, 2017. https:\/\/doi.org\/10.48550\/arXiv.1705.07874"},{"key":"e_1_3_8_19_2","doi-asserted-by":"publisher","DOI":"10.1183\/23120541.00471-2022"},{"key":"e_1_3_8_20_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2021.106395"},{"key":"e_1_3_8_21_2","first-page":"689","article-title":"[Chinese expert consensus on the diagnosis and treatment of chronic refractory cough]","volume":"44","author":"Asthma Group of Chinese Throacic S","year":"2021","unstructured":"Asthma Group of Chinese Throacic S. [Chinese expert consensus on the diagnosis and treatment of chronic refractory cough]. Zhonghua Jie He He Hu Xi Za Zhi 2021; 44: 689\u2013698. https:\/\/doi.org\/10.3760\/cma.j.cn112147-20210320-00186","journal-title":"Zhonghua Jie He He Hu Xi Za Zhi"},{"key":"e_1_3_8_22_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.0040297"},{"key":"e_1_3_8_23_2","doi-asserted-by":"publisher","DOI":"10.4168\/aair.2023.15.6.795"},{"key":"e_1_3_8_24_2","doi-asserted-by":"publisher","DOI":"10.1183\/09031936.94.07071246"},{"key":"e_1_3_8_25_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00408-010-9272-1"},{"key":"e_1_3_8_26_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1365-2036.2009.04142.x"},{"key":"e_1_3_8_27_2","doi-asserted-by":"publisher","DOI":"10.1136\/thorax.58.4.339"},{"key":"e_1_3_8_28_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.kint.2020.07.035"},{"key":"e_1_3_8_29_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eururo.2018.08.038"},{"key":"e_1_3_8_30_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.rmed.2022.106985"},{"key":"e_1_3_8_31_2","doi-asserted-by":"publisher","DOI":"10.1183\/23120541.00100-2023"},{"key":"e_1_3_8_32_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00408-024-00729-8"},{"key":"e_1_3_8_33_2","doi-asserted-by":"publisher","DOI":"10.1177\/17534666251360065"},{"key":"e_1_3_8_34_2","doi-asserted-by":"publisher","DOI":"10.1183\/23120541.00012-2021"},{"key":"e_1_3_8_35_2","doi-asserted-by":"publisher","DOI":"10.4081\/monaldi.2026.3767"},{"key":"e_1_3_8_36_2","doi-asserted-by":"publisher","DOI":"10.1038\/nrdp.2017.42"},{"key":"e_1_3_8_37_2","doi-asserted-by":"publisher","DOI":"10.1183\/23120541.00075-2022"}],"container-title":["Therapeutic Advances in Respiratory Disease"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/17534666261487594","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/17534666261487594","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/17534666261487594","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,13]],"date-time":"2026-09-13T16:17:26Z","timestamp":1789316246000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/17534666261487594"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":36,"alternative-id":["10.1177\/17534666261487594"],"URL":"https:\/\/doi.org\/10.1177\/17534666261487594","relation":{"has-review":[{"id-type":"doi","id":"10.1177\/17534666261487594\/v3\/decision1","asserted-by":"object"},{"id-type":"doi","id":"10.1177\/17534666261487594\/v1\/review2","asserted-by":"object"},{"id-type":"doi","id":"10.1177\/17534666261487594\/v1\/review1","asserted-by":"object"},{"id-type":"doi","id":"10.1177\/17534666261487594\/v2\/review1","asserted-by":"object"},{"id-type":"doi","id":"10.1177\/17534666261487594\/v3\/response1","asserted-by":"object"},{"id-type":"doi","id":"10.1177\/17534666261487594\/v2\/decision1","asserted-by":"object"},{"id-type":"doi","id":"10.1177\/17534666261487594\/v2\/response1","asserted-by":"object"},{"id-type":"doi","id":"10.1177\/17534666261487594\/v1\/decision1","asserted-by":"object"}]},"ISSN":["1753-4666","1753-4666"],"issn-type":[{"value":"1753-4666","type":"print"},{"value":"1753-4666","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9]]},"article-number":"17534666261487594"}}