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A. Thawer



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    Poster Display Session (ID 63)

    • Event: ELCC 2017
    • Type: Poster Display Session
    • Track:
    • Presentations: 1
    • Moderators:
    • Coordinates: 5/07/2017, 12:30 - 13:00, Hall 1
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      111P - Pharmacist led proactive follow-up algorithm for advanced EGFR positive NSCLC patients on afatinib (ID 513)

      12:30 - 13:00  |  Author(s): A. Thawer

      • Abstract

      Background:
      Afatinib is a standard first-line therapy for advanced EGFR positive NSCLC. We implemented a pharmacy led proactive follow-up algorithm for pts prescribed afatinib to identify and manage early adverse events (AEs) (Table). Management of AEs was standardized.

      Methods:
      This was a retrospective chart review of all advanced EGFR positive NSCLC pts at the Sunnybrook Odette Cancer Centre from April 1, 2015 to July 31, 2016 that received afatinib following institution of our algorithm. This study evaluated the impact of our algorithm and characteristics of real world AEs.

      Results:
      We included 33 pts. Median age was 64 and 55%, 79%, 59%, 27% and 88% were female, PS < 2, Asian, smokers, and treated as 1st line, respectively. Median follow up was 249 days (d). Median time on afatinib was 157 d (IQR: 27 to 304). Prophylactic use of topical hydrocortisone/clindamycin was 55% and 46% for an oral tetracycline. All pts had 1 drug related AE, 18% were grade 3/4. Most common AEs were diarrhea 88%, rash 82%, stomatitis 58%, paronychia 46%, nausea 39% and fatigue 39%. Median time to 1st drug related AE was 17 d (IQR: 7 to 126), with early median time to onset of diarrhea 8 d, stomatitis 13 d, rash 15 d, fatigue 18 d and nausea 25 d and late onset of paronychia 75 d, transaminitis 114 d and anorexia 133 d. Median dose of afatinib was 40 mg/daily, 34% of pts had > or = 1 dose reduction and 9% discontinued afatinib due to AEs. Proactive calls identified 37% of all drug related AEs, 33% of grade 3/4 AEs, 58% of first drug related AEs and identified 2 patients that were noncompliant. Only 3% of AEs were identified by an ER visit/urgent clinic visit.rnTable: 111PPhamacist led follow-up algorithm for pts prescribed afatinibrn

      rnrnrnrnrnrnrnrnrnrnrnrnrnrnrnrnrnrnrnrnrnrnrnrnrnrnrnrnrnrnrnrnrn rnrn
      Time on drugDay 1Day 5Day 10Day 14Day 17
      InterventionVisit with pharmacyProactive pharmacy callProactive pharmacy callRoutine clinic visit with medical oncologyProactive pharmacy call
      Variables assessedPatient education of side effects and consent obtained for proactive callsAdherence Rash Diarrhea StomatitisAdherence Rash Diarrhea Stomatitis Paronychia Nausea FatigueClinical assessment and laboratory monitoring of CBC, creatinine and liver function testsAdherence Rash Diarrhea Stomatitis Paronychia Nausea Fatigue Anorexia
      rn

      Conclusions:
      Our algorithm resulted in early identification and management of AEs with a low rate of urgent assessments and discontinuation due to toxicity while maintaining the ideal dose of afatinib. This algorithm provides a tool for centres prescribing afatinib.

      Clinical trial identification:


      Legal entity responsible for the study:
      Dr. Parneet Cheema, PI and Sunnybrook Health Sciences Centre

      Funding:
      Boehringer Ingelheim

      Disclosure:
      P.K. Cheema: Advisory board and research grants: Boehringer Ingelheim. A. Thawer: Advisory board and research grant: Boehringer Ingelheim. S.Y. Cheng, S. Khanna: Advisory board: Boehringer Ingelheim. All other authors have declared no conflicts of interest.