Evidence map›Paper›PMID 30116943›Full record

ArticleSupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer2019

Multi-disciplinary proactive follow-up algorithm for patients with advanced NSCLC receiving afatinib.

Parneet K Cheema, Alia Thawer, Joanne Leake, Susanna Y Cheng, Suneil Khanna, J Charles Victor

Abstract read
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Article in Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Assessment of diarrhea as side effect of oral targeted antineoplastic agents in clinical practice.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2021
    Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Parneet K CheemaSunnybrook Odette Cancer Centre, University of Toronto, Toronto, Canada. parneet.cheema@williamoslerhs.ca.ORCID http://orcid.org/0000-0002-9680-7073
Alia ThawerSunnybrook Odette Cancer Centre, University of Toronto, Toronto, Canada.
Joanne LeakeSunnybrook Odette Cancer Centre, University of Toronto, Toronto, Canada.
Susanna Y ChengSunnybrook Odette Cancer Centre, University of Toronto, Toronto, Canada.
Suneil KhannaSunnybrook Odette Cancer Centre, University of Toronto, Toronto, Canada.
J Charles VictorInstitute of Health Policy Management and Evaluation, University of Toronto, Toronto, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeAfatinib is a standard first-line therapy for advanced EGFR-positive NSCLC. We implemented a pharmacist-led proactive follow-up algorithm to identify and manage early afatinib-related adverse events (AEs).

methodsWe conducted a retrospective chart review of all patients treated with afatinib after implementation of the algorithm at the Sunnybrook Odette Cancer Centre (Toronto, ON, Canada) from April 1, 2015 to July 31, 2016. Our in-house algorithm involved consultations in person and proactive pharmacist-led callbacks on days 5, 10, and 17. All AEs were graded and documented in real time and management based on toxicity grade was standardized. This study evaluated the impact of our algorithm on real-world AEs. RESULTS AND DISCUSSION: Thirty-three patients were identified and reviewed. Median follow-up was 248 days. All patients experienced at least one drug-related AE; 18.2% were grade 3/4. The most common AEs were diarrhea 87.9%, rash 81.8%, stomatitis 57.6%, and paronychia 45.5%. Median dose of afatinib was 40 mg daily; 51.5% of patients had ≥ 1 dose reduction and 6.3% discontinued afatinib due to AEs. Proactive calls by the pharmacist identified 36.5% of all drug-related AEs, 33.3% of grade 3/4 AEs, 58.1% of first drug-related AEs and identified two patients that were non-compliant. Only 3.2% of AEs were identified by an emergency room/urgent clinic visit.

conclusionsThis proactive multi-disciplinary AE management algorithm resulted in a low rate of urgent assessments and discontinuation due to toxicity while maintaining afatinib at ideal dose, thus providing a useful tool for centers prescribing afatinib.

Indexed as

AlgorithmsAfatinibAgedAntineoplastic AgentsCanadaCarcinoma, Non-Small-Cell LungDiarrheaErbB ReceptorsExanthemaFemaleHumansLung NeoplasmsMaleMiddle AgedQuinazolinesRetrospective StudiesAfatinibAntineoplastic AgentsErbB ReceptorsQuinazolinesAdverse eventsAfatinibAlgorithmEGFRNSCLCProactive monitoring

Identifiers

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.