Author of

• 20039

  +

  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

  • 19867

    +

    111P - Pharmacist led proactive follow-up algorithm for advanced EGFR positive NSCLC patients on afatinib (ID 513)

    12:30 - 13:00  |  Author(s): J. Leake
    • 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 drug	Day 1	Day 5	Day 10	Day 14	Day 17
    Intervention	Visit with pharmacy	Proactive pharmacy call	Proactive pharmacy call	Routine clinic visit with medical oncology	Proactive pharmacy call
    Variables assessed	Patient education of side effects and consent obtained for proactive calls	Adherence Rash Diarrhea Stomatitis	Adherence Rash Diarrhea Stomatitis Paronychia Nausea Fatigue	Clinical assessment and laboratory monitoring of CBC, creatinine and liver function tests	Adherence 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.