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

Asif H Khan, Adeline Abbe, Bruno Falissard, Paulo Carita, Claus Bachert, Joaquim Mullol, Matthew Reaney, Jingdong Chao, Leda P Mannent, Nikhil Amin, Puneet Mahajan, Gianluca Pirozzi, Laurent Eckert, Asif H Khan, Adeline Abbe, Bruno Falissard, Paulo Carita, Claus Bachert, Joaquim Mullol, Matthew Reaney, Jingdong Chao, Leda P Mannent, Nikhil Amin, Puneet Mahajan, Gianluca Pirozzi, Laurent Eckert

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: CRSwNP; free-text data mining; patient perspective; self-assessment; sense of smell.

Conflict of interest statement

AHK, PC, LPM, PM, and LE are employees of Sanofi, and may hold stock and/or stock options in the company. AA, MR, and GP are former employees of Sanofi. JC and NA are employees of Regeneron Pharmaceuticals, Inc. and shareholders in the company. BF is a consultant for AbbVie, Actelion, Allergan, Almirall, Alnylam, Amgen, Astellas, AstraZeneca, Bayer, Biocodex, Biogen, Biopecs, Bioprojet, Biotronik, BMS, Boehringer Ingelheim, Celgène, Chiesi, D&A Pharma, Daiichi-Sankyo, Eisai, Eli Lilly, Ethypharm, Genevrier, Genzyme, Gilead, Grunenthal, GSK, HRA, IDM Pharma, Idorsia, Indivior, Janssen, Lundbeck, Léo, Menarini, Novonordisk, MSD, Novartis, Otsuka, Pfizer, Pierre Fabre, Recordati, Roche, Sanofi, Servier, Stallergenes Greer, Takeda, UCB, and ViiV. CB is an advisory board member for ALK, ASIT Biotech, AstraZeneca, Intrexon Actobiotics, Novartis, Sanofi, and Stallergenes Greer. JM is a member of national or international advisory boards, and received speaker fees or funding for clinical trials and research projects from ALK, AstraZeneca, Genentech, GSK, Glenmark, Menarini, Mitsubishi-Tanabe, MSD, Mylan-MEDA Pharma, Novartis, Regeneron Pharmaceuticals, Inc., Sanofi Genzyme, UCB Pharma, and Uriach Group. The authors report no other conflicts of interest in this work.

© 2021 Khan et al.

Figures

Figure 1
Figure 1
Word clouds in patients treated with (A) dupilumab or (B) placebo. Word cloud based on frequency (higher frequency = bigger font size). Only words that occur twice or more are shown. Stop words and the words “study” and “treatment” are omitted.
Figure 2
Figure 2
Co-occurrence of words in patients completing a self-assessment tool treated with (A) dupilumab, (B) placebo. Words in the same cluster were more frequently reported together. Colors identify word clusters.
Figure 3
Figure 3
Sentiment analysis of patients completing a self-assessment tool: overall, dupilumab group, and placebo group.

References

    1. Halpern J. From Detached Concern to Empathy: Humanizing Medical Practice. New York, NY: Oxford University Press; 2001.
    1. Greenhalgh T, Hurwitz B. Narrative based medicine: why study narrative? BMJ. 1999;318(7175):48–50. doi:10.1136/bmj.318.7175.48
    1. Doward LC, Gnanasakthy A, Baker MG. Patient reported outcomes: looking beyond the label claim. Health Qual Life Outcomes. 2010;8:89. doi:10.1186/1477-7525-8-89
    1. Hareendran A, Gnanasakthy A, Winnette R, Revicki D. Capturing patients’ perspectives of treatment in clinical trials/drug development. Contemp Clin Trials. 2012;33(1):23–28. doi:10.1016/j.cct.2011.09.015
    1. Messina J, Grainger DL. A pilot study to identify areas for further improvements in patient and public involvement in health technology assessments for medicines. Patient. 2012;5(3):199–211.
    1. Wagland R, Recio-Saucedo A, Simon M, et al. Development and testing of a text-mining approach to analyse patients’ comments on their experiences of colorectal cancer care. BMJ Qual Saf. 2016;25(8):604–614. doi:10.1136/bmjqs-2015-004063
    1. Weaver M, Patrick DL, Markson LE, et al. Issues in the measurement of satisfaction with treatment. Am J Manag Care. 1997;3(4):579–594.
    1. Regnault A, Balp MM, Kulich K, Viala-Danten M. Validation of the treatment satisfaction questionnaire for medication in patients with cystic fibrosis. J Cyst Fibros. 2012;11(6):494–501. doi:10.1016/j.jcf.2012.04.007
    1. Reaney M, Bush E, New M, et al. The potential role of individual-level benefit-risk assessment in treatment decision making: a DIA study endpoints community workstream. Ther Innov Regul Sci. 2019;53(5):630–638. doi:10.1177/2168479018807448
    1. Edwards P. Questionnaires in clinical trials: guidelines for optimal design and administration. Trials. 2010;11:2. doi:10.1186/1745-6215-11-2
    1. Falissard B, Simpson EL, Guttman-Yassky E, et al. Qualitative assessment of adult patients’ perception of atopic dermatitis using natural language processing analysis in a cross-sectional study. Dermatol Ther (Heidelb). 2020;10(2):297–305. doi:10.1007/s13555-020-00356-0
    1. Abbe A, Grouin C, Zweigenbaum P, Falissard B. Text mining applications in psychiatry: a systematic literature review. Int J Methods Psychiatr Res. 2016;25(2):86–100. doi:10.1002/mpr.1481
    1. Fokkens WJ, Lund VJ, Hopkins C, et al. European position paper on rhinosinusitis and nasal polyps 2020. Rhinology. 2020;58(Suppl S29):1–464. doi:10.4193/Rhin20.401
    1. Khan A, Huynh TMT, Vandeplas G, et al. The GALEN rhinosinusitis cohort: chronic rhinosinusitis with nasal polyps affects health-related quality of life. Rhinology. 2019;57(5):343–351.
    1. Palmer JN, Messina JC, Biletch R, et al. A cross-sectional, population-based survey of US adults with symptoms of chronic rhinosinusitis. Allergy Asthma Proc. 2019;40(1):48–56. doi:10.2500/aap.2019.40.4182
    1. Bhattacharyya N, Villeneuve S, Joish VN, et al. Cost burden and resource utilization in patients with chronic rhinosinusitis and nasal polyps. Laryngoscope. 2019;129(9):1969–1975. doi:10.1002/lary.27852
    1. Bachert C, Bhattacharyya N, Desrosiers M, Khan AH. Burden of disease in chronic rhinosinusitis with nasal polyps. J Asthma Allergy. 2021;14:127–134. doi:10.2147/JAA.S290424
    1. Oyer SL, Mulligan JK, Psaltis AJ, et al. Cytokine correlation between sinus tissue and nasal secretions among chronic rhinosinusitis and controls. Laryngoscope. 2013;123(12):E72–E78. doi:10.1002/lary.24305
    1. Miljkovic D, Bassiouni A, Cooksley C, et al. Association between group 2 innate lymphoid cells enrichment, nasal polyps and allergy in chronic rhinosinusitis. Allergy. 2014;69(9):1154–1161. doi:10.1111/all.12440
    1. Macdonald LE, Karow M, Stevens S, et al. Precise and in situ genetic humanization of 6 Mb of mouse immunoglobulin genes. Proc Natl Acad Sci U S A. 2014;111(14):5147–5152. doi:10.1073/pnas.1323896111
    1. Murphy AJ, Macdonald LE, Stevens S, et al. Mice with megabase humanization of their immunoglobulin genes generate antibodies as efficiently as normal mice. Proc Natl Acad Sci U S A. 2014;111(14):5153. doi:10.1073/pnas.1324022111
    1. Gandhi NA, Pirozzi G, Graham NMH. Commonality of the IL-4/IL-13 pathway in atopic diseases. Expert Rev Clin Immunol. 2017;13(5):425–437. doi:10.1080/1744666X.2017.1298443
    1. DUPIXENT® (dupilumab) injection [prescribing information]. Bridgewater, NJ; Tarrytown, NY: Sanofi-Aventis U.S. LLC; Regeneron Pharmaceuticals, Inc.; 2019.
    1. DUPIXENT® (dupilumab) injection [summary of product characteristics]. Paris, France: Sanofi-Aventis Groupe; 2017.
    1. Bachert C, Mannent L, Naclerio RM, et al. Effect of subcutaneous dupilumab on nasal polyp burden in patients with chronic sinusitis and nasal polyposis: a randomized clinical trial. JAMA. 2016;315(5):469–479. doi:10.1001/jama.2015.19330
    1. Bachert C, Han JK, Desrosiers M, et al. Efficacy and safety of dupilumab in patients with severe chronic rhinosinusitis with nasal polyps (LIBERTY NP SINUS-24 and LIBERTY NP SINUS-52): results from two multicentre, randomised, double-blind, placebo-controlled, parallel-group Phase 3 trials. Lancet. 2019;394(10209):1638–1650. doi:10.1016/S0140-6736(19)31881-1
    1. Bachert C, Hellings PW, Mullol J, et al. Dupilumab improves health-related quality of life in patients with chronic rhinosinusitis with nasal polyposis. Allergy. 2020;75(1):148–157. doi:10.1111/all.13984
    1. Locke S, Bashall A, Al-Adely S, et al. Natural language processing in medicine: a review. Trends Anaesth Crit Care. 2021;38:4–9. doi:10.1016/j.tacc.2021.02.007
    1. de Hollander G, Marx M. Summarization of meetings using word clouds. In computer science and software engineering (CSSE). Paper presented at: CSI International Symposium 2011. IEEE; 2011:54–61.
    1. Newman ME. Fast algorithm for detecting community structure in networks. Phys Rev E Stat Nonlin Soft Matter Phys. 2004;69(6 Pt 2):066133. doi:10.1103/PhysRevE.69.066133
    1. Clauset A, Newman MEJ, Moore C. Finding community structure in very large networks. Phys Rev E. 2004;70(6):066111. doi:10.1103/PhysRevE.70.066111
    1. Levy JM, Mace JC, Bodner TE, et al. Defining the minimal clinically important difference for olfactory outcomes in the surgical treatment of chronic rhinosinusitis. Int Forum Allergy Rhinol. 2017;7(8):821–826. doi:10.1002/alr.21964
    1. Sindwani R, Han JK, Soteres DF, et al. Navigate i: randomized, placebo-controlled, double-blind trial of the exhalation delivery system with fluticasone for chronic rhinosinusitis with nasal polyps. Am J Rhinol Allergy. 2019;33(1):69–82. doi:10.1177/1945892418810281
    1. Ricci-Cabello I, Saletti-Cuesta L, Slight SP, Valderas JM. Identifying patient-centred recommendations for improving patient safety in general practices in England: a qualitative content analysis of free-text responses using the patient reported experiences and outcomes of safety in primary care (PREOS-PC) questionnaire. Health Expect. 2017;20(5):961–972.
    1. Vehviläinen-Julkunen K, Turpeinen S, Kvist T, et al. Experience of ambulatory cancer care: understanding patients’ perspectives of quality using sentiment analysis. Cancer Nurs. 2021;44(6):E331–8. doi:10.1097/NCC.0000000000000845
    1. Shu CH, Lee PO, Lan MY, Lee YL. Factors affecting the impact of olfactory loss on the quality of life and emotional coping ability. Rhinology. 2011;49(3):337–341. doi:10.4193/Rhino10.130
    1. Alt JA, Mace JC, Buniel MC, et al. Predictors of olfactory dysfunction in rhinosinusitis using the brief smell identification test. Laryngoscope. 2014;124(7):E259–E266. doi:10.1002/lary.24587
    1. Mattos JL, Schlosser RJ, Storck KA, Soler ZM. Understanding the relationship between olfactory-specific quality of life, objective olfactory loss, and patient factors in chronic rhinosinusitis. Int Forum Allergy Rhinol. 2017;7(7):734–740. doi:10.1002/alr.21940
    1. O’Cathain A, Thomas KJ. “Any other comments?” Open questions on questionnaires - A bane or a bonus to research? BMC Med Res Methodol. 2004;4:25. doi:10.1186/1471-2288-4-25
    1. Greaves F, Ramirez-Cano D, Millett C, et al. Use of sentiment analysis for capturing patient experience from free-text comments posted online. J Med Internet Res. 2013;15(11):e239. doi:10.2196/jmir.2721
    1. Dambha-Miller H, Silarova B, Irving G, et al. Patients’ views on interactions with practitioners for type 2 diabetes: a longitudinal qualitative study in primary care over 10 years. Br J Gen Pract. 2018;68(666):e36–e43. doi:10.3399/bjgp17X693917

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