Tara Herrmann, PhD1; Pamela Peters, PhD1; Chad Williamson, MS, MBA2; Evan Rhodes, MBA2; Daniel Morgensztern, MD3; Ramaswamy Govindan, MD3 1Medscape, LLC, New York, NY, USA; 2CE Outcomes, LLC, Birmingham, AL, USA; 3Washington University School of Medicine, St. Louis, MO, USA

Advanced NSCLC: Finding the Right Prescription for Oncologist Education Advanced NSCLC: Finding the Right Prescription for Oncologist Education

introduction

Lung cancer is the leading cause of cancer-related death in the United States. In 2014, an estimated 159,000 deaths are predicted and more than 220,000 individuals are expected to receive a diagnosis of lung cancer.1 Moreover, despite developments in care for patients with advanced lung cancer, outcomes remain poor, with 5-year survival rates remaining below 20%.2

Since 2006, a steady stream of data has demonstrated that advanced non-small cell lung cancer (NSCLC) cannot be considered or treated as a single disease entity. Rather, advanced NSCLC must be seen as a heterogeneous condition that is divided into histological and molecular subtypes with dedicated targeted and chemotherapeutic strategies.3 The ability to use tumor-specific characteristics to make treatment decisions has revolutionized the landscape for lung cancer care and research. As a result, most NSCLC experts find the diagnosis of NSCLC, not otherwise specified (NOS) to be largely unacceptable.4,5

Despite this, numerous data sources continue to reveal deficits in physicians’ knowledge, skills, and confidence related to the application of relevant clinical, histologic, and genomic characterization of tumors to treatment decisions for patients with advanced NSCLC.6-12 The objective of this study was to evaluate the impact of a baseline case-vignette assessment13,14 followed by a personalized education plan that aimed to narrow gaps in the clinical practices of oncologists who care for patients with advanced NSCLC.

methods

This educational initiative comprised a baseline self-assessment and 5 CME-certified activities. Learner-directed assessment questions were aligned with the learning objectives of 1 or more of the 5 educational activities.

• Content of individual activities addressed knowledge and practice gaps identified in the needs assessment.

• Assessment questions were repeated within activities to serve as a post-assessment for the education.

• Content addressed identified physician knowledge and clinical practice gaps.

Learners began the initiative by completing the self-assessment case vignettes to provide an assessment of baseline knowledge and practice patterns.

Immediate personalized feedback and an individualized educational plan were provided upon each participant’s completion of the self-assessment. Included within each individualized plan were:

• Online links to the prescribed activities; and

• A tailored communication and educational reinforcement plan to encourage continued participant engagement through the completion of the program.

The baseline self-assessment and the educational activities were posted online simultaneously.

After learners received their personalized learning plan, they participated in the prescribed activities, wherein they responded to post-assessment questions at the conclusion of each educational activity. Each activity contained 2 post-activity questions derived from the baseline self-assessment instrument. Responses to the questions were collected and aggregated for comparative analysis of the post-assessment responses relative to the participants’ baseline self-assessment responses to aligned questions. This aggregate comparison served as a measure of the impact of the educational activity in improving the knowledge, skill, or performance of participating physicians. Non-practicing oncologists as well as oncologists who were not currently managing any patients with advanced NSCLC were excluded from the study.

In total, 92 oncologists completed their individualized learning plans. Oncologists participating in the personalized learning saw an average of 9 patients with advanced NSCLC per week, with 52% seeing 1 to 5 new patients with advanced disease per month.

This personalized learning intervention was associated with an effect size of 0.70, exceeding the recognized medium effect size standard of 0.45 to 0.50. Specific educational impact findings include:

• 13% improvement over baseline in ability to identify the rationale for determining the histological subtype of NSCLC;

• 87% of oncologists (compared with 33% at baseline, P=0.01) were aware of which patients could be considered for maintenance therapy; and

• 97% (compared with 76% at baseline, P=0.04) were able to correctly identify the prevalence of specific genetic abnormalities.

results

Conclusions

With an overall effect size of 0.7, this study demonstrates the feasibility of a personalized, targeted educational intervention for improving practice patterns of oncologists treating patients with advanced NSCLC. However, there remain several post-education gaps in the management of advanced NSCLC, including:

• 27% of oncologists would still inappropriately prescribe a bevacizumab- and/or pemetrexed-containing regimen in a 59-year-old male smoker with advanced NSCLC, squamous cell carcinoma;

• Almost 30% of oncologists still incorrectly identified EGFR mutations and ALK translocations as being more prevalent than KRAS mutations. In an era where molecular profiling is still a work in progress, but cost effectiveness is of high importance, it is critical that oncologists are able to identify which mutations, and therefore which tests, are most relevant for their patients in order to maximize outcomes while minimizing costs15,16, and

• 35% of oncologists would still prescribe erlotinib based on clinical factors rather than on mutational testing, in stark contrast to the 2011 provisional opinion by the American Society of Clinical Oncology.14

Additional novel, personalized educational programs need to be developed to continue to improve the physician learning experience in this era of personalized medicine for advanced NSCLC.

References

1. Siegel R, Ma J, Zou Z, Jemal A. Cancer statistics, 2014. CA Cancer J Clin. 2014;64:9-29.

2. American Cancer Society (ACS). Lung cancer (non-small cell): what are the key statistics about lung cancer? Revised April 30, 2014. http://www.cancer.org/Cancer/LungCancer-Non-SmallCell/DetailedGuide/non-small-cell-lung-cancer-key-statistics Accessed April 8, 2014.

3. National Comprehensive Cancer Network (NCCN) Non-Small Cell Lung Cancer Guidelines. V3.2014. www.nccn.org. Accessed April 8, 2014.

4. Travis WD, Brambilla E, Noguchi M, et al. International Association for the Study of Lung Cancer/American Thoracic society/European Respiratory Society: international multidisciplinary classification of lung adenocarcinoma. J Thorac Oncol. 2011;6:244-285.

5. Lindeman NI, Cagle PT, Beasley MB, et al. Molecular testing guideline for selection of lung cancer patients for EGFR and ALK tyrosine kinase inhibitors: guideline from the College of American Pathologists, International Association for the Study of Lung Cancer, and Association for Molecular Pathology. J Thorac Oncol. 2013;8:823-859.

6. Medscape Education Survey. Challenges in the Treatment of Non-Small Cell Lung Cancer. September 2013. Data on file. Accessed March 24, 2014.

7. Medscape Oncology. Advanced NSCLC: A Personalized Learning Initiative. Personalized Learning Impact Report. http://www.medscape.org/personalized-learning/6004655 October 29, 2013. Data on file. Accessed March 25, 2014.

8. Nadjafi M, Santos GDC, Le L, et al. Diagnostic patterns of NSCLC at Princess Margaret Hospital. J Clin Oncol. 2011;29(Suppl):Abstract e18027.

9. Ou SH, Zell JA. Carcinoma NOS is a common histologic diagnosis and is increasing in proportion among non-small cell lung cancer histologies. J Thorac Oncol. 2009;4:1202-1211.

10. Shaw AT. Personalizing Treatment for NSCLC: Going Beyond the Ordinary. Medscape Education Oncology. October 1, 2013. http://www.medscape.org/viewarticle/811052 Accessed March 24, 2014.

11. Sulpher JA, Owen SP, Hon H, et al. Factors influencing a specific histologic diagnosis of non-small cell lung cancer. J Clin Oncol. 2011;29(Suppl):Abstract 7541.

12. Peabody JW, Luck J, Glassman P, Dresselhaus TR, Lee M. Comparison of vignettes, standardized patients, and chart abstraction: a prospective validation study of 3 methods for measuring quality. JAMA. 2000;283:1715-1722.

13. Peabody JW, Luck J, Glassman P, et al. Measuring the quality of physician practice by using clinical vignettes: a prospective validation study. Ann Intern Med. 2004;141:771-780.

14. Keedy VL, Temin S, Somerfield MR, et al. American Society of Clinical Oncology provisional clinical opinion: epidermal growth factor receptor (EGFR) mutation testing for patients with advanced non-small-cell lung cancer considering first-line EGFR tyrosine kinase inhibitor therapy. J Clin Oncol. 2011;29:2121-2127.

15. de Lima Lopes G Jr, Segel JE, Tan DS, Do YK, Mok T, Finkelstein EA. Cost-effectiveness of epidermal growth factor receptor mutation testing and first-line treatment with gefitinib for patients with advanced adenocarcinoma of the lung. Cancer. 2012;118:1032-1039.

16. Adamson RT. Biomarkers and molecular profiling in non-small cell lung cancer: an expanding role and its managed care implications. Am J Manag Care. 2013;19:S398-S404.

Acknowledgements

The Clinical Practice Assessment (baseline self-assessment instrument) was funded, in part, through an independent educational grant from Eli Lilly and Genentech. Review and editorial help was provided by Kathleen Geissel, PharmD, Rachel Myers, MPH, and Christopher Clarke, all of Medscape Education.

For more information, contact:

Tara Herrmann, PhDDirector, Educational Strategy, Medscape, LLC therrmann@medscape.net

figure 1 Treatment selection for a lifelong nonsmoking woman with lung adenocarcinoma, unknown epidermal growth factor receptor (EGFR) status.

Erlotinib Gemcitabine and cisplatin Gemcitabine, cisplatin, and bevacizumab

Paclitaxel, carboplatin, and bevacizumab*

Pre-Assessment (n=37) Post-assessment (n=37)100%

80%

60%

40%

20%

0%

54%

11% 11%

24%35%

8%

0%

57%

*P =.003

A 65-year-old woman presented to you with complaints of chronic cough. She and her husband have been lifelong nonsmokers. Biopsy of the lung mass was positive for moderately differentiated adenocarcinoma. Her past medical history included well-controlled hypertension and a mild cerebrovascular accident in the past. Her Eastern Cooperative Oncology Group (ECOG) performance status was 1.

Based on the available information, which treatment regimen would you choose for this patient?

figure 3 Testing included for a patient whose biopsy results suggest lung adenocarcinoma.

ALK and EGFR* ALK and K-Ras ALK and HER EGFR and K-Ras

Pre-Assessment (n=29) Post-assessment (n=29)100%

80%

60%

40%

20%

0%

76%

7%3%

14%

97%

3%0% 0%

*P <.01

figure 2 Treatment selection for a patient with stage IV adenocarcinoma, very symptomatic with hemoptysis.

Erlotinib Pemetrexed and carboplatin* Gemcitabine and cisplatin Paclitaxel, carboplatin, and bevacizumab

Pre-Assessment (n=37) Post-assessment (n=37)100%

80%

60%

40%

20%

0%

5%

32%

16%

46%

3%

76%

11% 11%

*P <.001

A 63-year-old woman had smoked a pack of cigarettes every 3 days for 15 years but quit 30 years ago. She presented with fatigue, weight loss, and hemoptysis. Evaluation revealed stage IV lung adenocarcinoma. The lung biopsy specimen was sent for molecular marker studies, which takes 2 to 3 weeks for the results to be returned.

Which treatment regimen would you recommend, based on the information available right now?

figure 4 Next step for a patient who started therapy prior to molecular test results, now results indicate EGFR mutation after receiving 2 cycles of therapy.

Change to erlotinib Continue for a total of 4 cycles of chemotherapy*

Add erlotinib to the chemotherapy treatment

regimen

Change to afatinib

Pre-Assessment (n=29) Post-assessment (n=29)100%

80%

60%

40%

20%

0%

34%

55%

10%

0%

7%

86%

3% 3%

*P =.001