Impact of an interactive on-line tool on therapeutic decision-making for patients with advanced non-small-cell lung cancer

Helen Chow, Martin J. Edelman, Giuiseppe Giaccone, Suresh S. Ramalingam, Timothy A. Quill, Andrew D. Bowser, Jim Mortimer, Wilma Guerra, Laurel A Beckett, Howard L. West, Primo N Lara, David R Gandara

Research output: Contribution to journalArticle

Abstract

Background: Treatment guidelines provide recommendations but cannot account for the wide variability in patient-tumor characteristics in individual patients. We developed an on-line interactive decision tool to provide expert recommendations for specific patient scenarios in the first-line and maintenance settings for advanced non-small-cell lung cancer. We sought to determine how providing expert feedback would influence clinical decision-making. Method: Five lung cancer experts selected treatment for 96 different patient cases based on patient and/or tumor-specific features. These data were used to develop an on-line decision tool. Participant physicians entered variables for their patient scenario with treatment choices, and then received expert treatment recommendations for that scenario. To determine the impact on decision-making, users were asked whether the expert feedback impacted their original plan. Results: A total of 442 individual physicians, of which 88% were from outside the United States, entered 653 cases, with report on impact in 389 cases. Expert feedback affected treatment choice in 73% of cases (23% changed and 50% confirmed decisions). For cases with epidermal growth factor receptor (EGFR) mutation or anaplastic lymphoma kinase (ALK) fusion, all experts selected targeted therapy whereas 51% and 58% of participants did not. Greater variability was seen between experts and participants for cases involving EGFR or ALK wild-type tumors. Participants were 2.5-fold more likely to change to expert recommended therapy for ALK fusions than for EGFR mutations (p = 0.017). Conclusion: This online tool for treatment decision-making resulted in a positive influence on clinician's decisions. This approach offers opportunities for improving quality of care and meets an educational need in application of new therapeutic paradigms.

Original languageEnglish (US)
Pages (from-to)1421-1429
Number of pages9
JournalJournal of Thoracic Oncology
Volume10
Issue number10
DOIs
StatePublished - Oct 1 2015

Fingerprint

Non-Small Cell Lung Carcinoma
Decision Making
Epidermal Growth Factor Receptor
Therapeutics
Physicians
Neoplasms
Mutation
Quality of Health Care
Lung Neoplasms
Maintenance
Guidelines
anaplastic lymphoma kinase

Keywords

  • Advanced non-small-cell lung cancer
  • Interactive online tool
  • Therapeutic decision-making

ASJC Scopus subject areas

  • Oncology
  • Pulmonary and Respiratory Medicine

Cite this

Impact of an interactive on-line tool on therapeutic decision-making for patients with advanced non-small-cell lung cancer. / Chow, Helen; Edelman, Martin J.; Giaccone, Giuiseppe; Ramalingam, Suresh S.; Quill, Timothy A.; Bowser, Andrew D.; Mortimer, Jim; Guerra, Wilma; Beckett, Laurel A; West, Howard L.; Lara, Primo N; Gandara, David R.

In: Journal of Thoracic Oncology, Vol. 10, No. 10, 01.10.2015, p. 1421-1429.

Research output: Contribution to journalArticle

Chow, Helen ; Edelman, Martin J. ; Giaccone, Giuiseppe ; Ramalingam, Suresh S. ; Quill, Timothy A. ; Bowser, Andrew D. ; Mortimer, Jim ; Guerra, Wilma ; Beckett, Laurel A ; West, Howard L. ; Lara, Primo N ; Gandara, David R. / Impact of an interactive on-line tool on therapeutic decision-making for patients with advanced non-small-cell lung cancer. In: Journal of Thoracic Oncology. 2015 ; Vol. 10, No. 10. pp. 1421-1429.
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abstract = "Background: Treatment guidelines provide recommendations but cannot account for the wide variability in patient-tumor characteristics in individual patients. We developed an on-line interactive decision tool to provide expert recommendations for specific patient scenarios in the first-line and maintenance settings for advanced non-small-cell lung cancer. We sought to determine how providing expert feedback would influence clinical decision-making. Method: Five lung cancer experts selected treatment for 96 different patient cases based on patient and/or tumor-specific features. These data were used to develop an on-line decision tool. Participant physicians entered variables for their patient scenario with treatment choices, and then received expert treatment recommendations for that scenario. To determine the impact on decision-making, users were asked whether the expert feedback impacted their original plan. Results: A total of 442 individual physicians, of which 88{\%} were from outside the United States, entered 653 cases, with report on impact in 389 cases. Expert feedback affected treatment choice in 73{\%} of cases (23{\%} changed and 50{\%} confirmed decisions). For cases with epidermal growth factor receptor (EGFR) mutation or anaplastic lymphoma kinase (ALK) fusion, all experts selected targeted therapy whereas 51{\%} and 58{\%} of participants did not. Greater variability was seen between experts and participants for cases involving EGFR or ALK wild-type tumors. Participants were 2.5-fold more likely to change to expert recommended therapy for ALK fusions than for EGFR mutations (p = 0.017). Conclusion: This online tool for treatment decision-making resulted in a positive influence on clinician's decisions. This approach offers opportunities for improving quality of care and meets an educational need in application of new therapeutic paradigms.",
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AU - Edelman, Martin J.

AU - Giaccone, Giuiseppe

AU - Ramalingam, Suresh S.

AU - Quill, Timothy A.

AU - Bowser, Andrew D.

AU - Mortimer, Jim

AU - Guerra, Wilma

AU - Beckett, Laurel A

AU - West, Howard L.

AU - Lara, Primo N

AU - Gandara, David R

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N2 - Background: Treatment guidelines provide recommendations but cannot account for the wide variability in patient-tumor characteristics in individual patients. We developed an on-line interactive decision tool to provide expert recommendations for specific patient scenarios in the first-line and maintenance settings for advanced non-small-cell lung cancer. We sought to determine how providing expert feedback would influence clinical decision-making. Method: Five lung cancer experts selected treatment for 96 different patient cases based on patient and/or tumor-specific features. These data were used to develop an on-line decision tool. Participant physicians entered variables for their patient scenario with treatment choices, and then received expert treatment recommendations for that scenario. To determine the impact on decision-making, users were asked whether the expert feedback impacted their original plan. Results: A total of 442 individual physicians, of which 88% were from outside the United States, entered 653 cases, with report on impact in 389 cases. Expert feedback affected treatment choice in 73% of cases (23% changed and 50% confirmed decisions). For cases with epidermal growth factor receptor (EGFR) mutation or anaplastic lymphoma kinase (ALK) fusion, all experts selected targeted therapy whereas 51% and 58% of participants did not. Greater variability was seen between experts and participants for cases involving EGFR or ALK wild-type tumors. Participants were 2.5-fold more likely to change to expert recommended therapy for ALK fusions than for EGFR mutations (p = 0.017). Conclusion: This online tool for treatment decision-making resulted in a positive influence on clinician's decisions. This approach offers opportunities for improving quality of care and meets an educational need in application of new therapeutic paradigms.

AB - Background: Treatment guidelines provide recommendations but cannot account for the wide variability in patient-tumor characteristics in individual patients. We developed an on-line interactive decision tool to provide expert recommendations for specific patient scenarios in the first-line and maintenance settings for advanced non-small-cell lung cancer. We sought to determine how providing expert feedback would influence clinical decision-making. Method: Five lung cancer experts selected treatment for 96 different patient cases based on patient and/or tumor-specific features. These data were used to develop an on-line decision tool. Participant physicians entered variables for their patient scenario with treatment choices, and then received expert treatment recommendations for that scenario. To determine the impact on decision-making, users were asked whether the expert feedback impacted their original plan. Results: A total of 442 individual physicians, of which 88% were from outside the United States, entered 653 cases, with report on impact in 389 cases. Expert feedback affected treatment choice in 73% of cases (23% changed and 50% confirmed decisions). For cases with epidermal growth factor receptor (EGFR) mutation or anaplastic lymphoma kinase (ALK) fusion, all experts selected targeted therapy whereas 51% and 58% of participants did not. Greater variability was seen between experts and participants for cases involving EGFR or ALK wild-type tumors. Participants were 2.5-fold more likely to change to expert recommended therapy for ALK fusions than for EGFR mutations (p = 0.017). Conclusion: This online tool for treatment decision-making resulted in a positive influence on clinician's decisions. This approach offers opportunities for improving quality of care and meets an educational need in application of new therapeutic paradigms.

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