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Data mining of free-text responses : an innovative approach to analyzing patient perspectives on treatment for chronic rhinosinusitis with nasal polyps in a phase IIa proof-of-concept study for dupilumab

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Abstract
Purpose: Patient perspective is an important and increasingly sought-after complement to clinical assessment. The aim of this study was to transcribe individual patients' experience of treatment in a dupilumab clinical trial through free-text responses with analysis using natural language processing (NLP) to obtain the unique perspective of patients on disease impact and unmet needs with existing treatment to inform future trial design. Patients and Methods: Patients with chronic rhinosinusitis with nasal polyps (CRSwNP) who were enrolled in a Phase IIa randomized controlled trial comparing dupilumab with placebo (NCT01920893) were invited to complete a self-assessment of treatment (SAT) tool at the end of treatment, asking, "What is your opinion on the treatment you had during the trial? What did you like or dislike about the treatment?" Free-text responses were analyzed for the overall cohort and according to treatment assignment using natural language processing including sentiment scoring. In a mixed-methods approach, quantitative patient-reported outcome (PRO) results were utilized to complement the qualitative analysis of free-text responses. Results: Of 60 patients enrolled in the study, 43 (71.6%) completed the SAT and responses from 37 patients were analyzed (placebo, n = 16; dupilumab, n = 21). Word analyses showed that the most common words were "smell," "improve," "staff," "great," "time," and "good." Across the whole cohort, "smell" was the most common symptom-related word. The words "smell" and "experience" were more likely to occur in patients treated with dupilumab. Patients treated with dupilumab also had more positive sentiment in their SAT responses than those who received placebo. The results from this qualitative analysis were reflected in quantitative PRO results. Conclusion: "Smell" was important to patients with CRSwNP, highlighting its importance as a patient-centric efficacy outcome measure in the context of clinical trials in CRSwNP. Trial Registration: ClinicalTrials.gov, NCT01920893. Registered 12 August 2013, https:// www.clinicaltrials.gov/ct2/show/NCT01920893.
Keywords
Health Policy, Pharmacology, Toxicology and Pharmaceutics (miscellaneous), Social Sciences (miscellaneous), Medicine (miscellaneous), CRSwNP, free-text data mining, patient perspective, self-assessment, sense of smell, OLFACTORY LOSS, PRIMARY-CARE, HUMANIZATION, SATISFACTION, EXPERIENCES, MEDICINE, OUTCOMES, LIFE

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MLA
Khan, Asif H., et al. “Data Mining of Free-Text Responses : An Innovative Approach to Analyzing Patient Perspectives on Treatment for Chronic Rhinosinusitis with Nasal Polyps in a Phase IIa Proof-of-Concept Study for Dupilumab.” PATIENT PREFERENCE AND ADHERENCE, vol. 15, 2021, pp. 2577–86, doi:10.2147/ppa.s320242.
APA
Khan, A. H., Abbe, A., Falissard, B., Carita, P., Bachert, C., Mullol, J., … Eckert, L. (2021). Data mining of free-text responses : an innovative approach to analyzing patient perspectives on treatment for chronic rhinosinusitis with nasal polyps in a phase IIa proof-of-concept study for dupilumab. PATIENT PREFERENCE AND ADHERENCE, 15, 2577–2586. https://doi.org/10.2147/ppa.s320242
Chicago author-date
Khan, Asif H, Adeline Abbe, Bruno Falissard, Paulo Carita, Claus Bachert, Joaquim Mullol, Matthew Reaney, et al. 2021. “Data Mining of Free-Text Responses : An Innovative Approach to Analyzing Patient Perspectives on Treatment for Chronic Rhinosinusitis with Nasal Polyps in a Phase IIa Proof-of-Concept Study for Dupilumab.” PATIENT PREFERENCE AND ADHERENCE 15: 2577–86. https://doi.org/10.2147/ppa.s320242.
Chicago author-date (all authors)
Khan, Asif H, Adeline Abbe, Bruno Falissard, Paulo Carita, Claus Bachert, Joaquim Mullol, Matthew Reaney, Jingdong Chao, Leda P Mannent, Nikhil Amin, Puneet Mahajan, Gianluca Pirozzi, and Laurent Eckert. 2021. “Data Mining of Free-Text Responses : An Innovative Approach to Analyzing Patient Perspectives on Treatment for Chronic Rhinosinusitis with Nasal Polyps in a Phase IIa Proof-of-Concept Study for Dupilumab.” PATIENT PREFERENCE AND ADHERENCE 15: 2577–2586. doi:10.2147/ppa.s320242.
Vancouver
1.
Khan AH, Abbe A, Falissard B, Carita P, Bachert C, Mullol J, et al. Data mining of free-text responses : an innovative approach to analyzing patient perspectives on treatment for chronic rhinosinusitis with nasal polyps in a phase IIa proof-of-concept study for dupilumab. PATIENT PREFERENCE AND ADHERENCE. 2021;15:2577–86.
IEEE
[1]
A. H. Khan et al., “Data mining of free-text responses : an innovative approach to analyzing patient perspectives on treatment for chronic rhinosinusitis with nasal polyps in a phase IIa proof-of-concept study for dupilumab,” PATIENT PREFERENCE AND ADHERENCE, vol. 15, pp. 2577–2586, 2021.
@article{8743317,
  abstract     = {{Purpose: Patient perspective is an important and increasingly sought-after complement to clinical assessment. The aim of this study was to transcribe individual patients' experience of treatment in a dupilumab clinical trial through free-text responses with analysis using natural language processing (NLP) to obtain the unique perspective of patients on disease impact and unmet needs with existing treatment to inform future trial design. Patients and Methods: Patients with chronic rhinosinusitis with nasal polyps (CRSwNP) who were enrolled in a Phase IIa randomized controlled trial comparing dupilumab with placebo (NCT01920893) were invited to complete a self-assessment of treatment (SAT) tool at the end of treatment, asking, "What is your opinion on the treatment you had during the trial? What did you like or dislike about the treatment?" Free-text responses were analyzed for the overall cohort and according to treatment assignment using natural language processing including sentiment scoring. In a mixed-methods approach, quantitative patient-reported outcome (PRO) results were utilized to complement the qualitative analysis of free-text responses. Results: Of 60 patients enrolled in the study, 43 (71.6%) completed the SAT and responses from 37 patients were analyzed (placebo, n = 16; dupilumab, n = 21). Word analyses showed that the most common words were "smell," "improve," "staff," "great," "time," and "good." Across the whole cohort, "smell" was the most common symptom-related word. The words "smell" and "experience" were more likely to occur in patients treated with dupilumab. Patients treated with dupilumab also had more positive sentiment in their SAT responses than those who received placebo. The results from this qualitative analysis were reflected in quantitative PRO results. Conclusion: "Smell" was important to patients with CRSwNP, highlighting its importance as a patient-centric efficacy outcome measure in the context of clinical trials in CRSwNP. Trial Registration: ClinicalTrials.gov, NCT01920893. Registered 12 August 2013, https:// www.clinicaltrials.gov/ct2/show/NCT01920893.}},
  author       = {{Khan, Asif H and Abbe, Adeline and Falissard, Bruno and Carita, Paulo and Bachert, Claus and Mullol, Joaquim and Reaney, Matthew and Chao, Jingdong and Mannent, Leda P and Amin, Nikhil and Mahajan, Puneet and Pirozzi, Gianluca and Eckert, Laurent}},
  issn         = {{1177-889X}},
  journal      = {{PATIENT PREFERENCE AND ADHERENCE}},
  keywords     = {{Health Policy,Pharmacology,Toxicology and Pharmaceutics (miscellaneous),Social Sciences (miscellaneous),Medicine (miscellaneous),CRSwNP,free-text data mining,patient perspective,self-assessment,sense of smell,OLFACTORY LOSS,PRIMARY-CARE,HUMANIZATION,SATISFACTION,EXPERIENCES,MEDICINE,OUTCOMES,LIFE}},
  language     = {{eng}},
  pages        = {{2577--2586}},
  title        = {{Data mining of free-text responses : an innovative approach to analyzing patient perspectives on treatment for chronic rhinosinusitis with nasal polyps in a phase IIa proof-of-concept study for dupilumab}},
  url          = {{http://doi.org/10.2147/ppa.s320242}},
  volume       = {{15}},
  year         = {{2021}},
}

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