Evidence map›Paper›PMID 39283351›Full record

ArticleSupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer2024

Optimizing inpatient care for lung cancer patients with immune checkpoint inhibitor-related pneumonitis using a clinical care pathway algorithm.

Norman Brito-Dellan, Maria Cecilia Franco-Vega, Juan Ignacio Ruiz, Maggie Lu, Hadeel Sahar, Pramuditha Rajapakse, Heather Y Lin, Christine Peterson, Daniel Leal-Alviarez, Haider Altay and 2 more

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Article in Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Norman Brito-Dellan *Department of Hospital Medicine, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1465, Houston, TX, 77030-40098, USA. nbrito@mdanderson.org.
Maria Cecilia Franco-Vega *Department of Hospital Medicine, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1465, Houston, TX, 77030-40098, USA.
Juan Ignacio RuizDepartment of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Maggie LuPharmacy Clinical Programs, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Hadeel SaharDepartment of Hospital Medicine, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1465, Houston, TX, 77030-40098, USA.
Pramuditha RajapakseUniversity of Massachusetts Chan Medical School, Worcester, MA, USA.
Heather Y LinDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Christine PetersonDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Daniel Leal-AlviarezDepartment of Hospital Medicine, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1465, Houston, TX, 77030-40098, USA.
Haider AltayDepartment of Hematology and Medical Oncology, The University of Texas Health Science Center at Tyler, Tyler, TX, USA.
Sophy TomyDepartment of Hospital Medicine, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1465, Houston, TX, 77030-40098, USA.
Joanna-Grace Mayo Manzano *Department of Hospital Medicine, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1465, Houston, TX, 77030-40098, USA.

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI DIANE BODURKA · 1985 to 2026
$290.8M
National Institutes of Health/National Cancer Institute Award number P30CA 016672
6 · The paper itself

Abstract

purposeImmune checkpoint inhibitor-related pneumonitis (ICI-P) is a condition associated with high mortality, necessitating prompt recognition and treatment initiation. This study aimed to assess the impact of implementing a clinical care pathway algorithm on reducing the time to treatment for ICI-P.

methodsPatients with lung cancer and suspected ICI-P were enrolled, and a multimodal intervention promoting algorithm use was implemented in two phases. Pre- and post-intervention analyses were conducted to evaluate the primary outcome of time from ICI-P diagnosis to treatment initiation.

resultsOf the 82 patients admitted with suspected ICI-P, 73.17% were confirmed to have ICI-P, predominantly associated with non-small cell lung cancer (91.67%) and stage IV disease (95%). Pembrolizumab was the most commonly used immune checkpoint inhibitor (55%). The mean times to treatment were 2.37 days in the pre-intervention phase, 3.07 days (p = 0.46), and 1.27 days (p = 0.40) in the post-intervention phases 1 and 2, respectively. Utilization of the immunotoxicity order set significantly increased from 0 to 27.27% (p = 0.04) after phase 2. While there were no significant changes in ICU admissions or inpatient mortality, outpatient pulmonology follow-ups increased statistically significantly, demonstrating enhanced continuity of care. The overall mortality for patients with ICI-P was 22%, underscoring the urgency of optimizing management strategies. Notably, all patients discharged on high-dose corticosteroids received appropriate gastrointestinal prophylaxis and prophylaxis against Pneumocystis jirovecii pneumonia infections at the end of phase 2.

conclusionImplementing a clinical care pathway algorithm for managing severe ICI-P in hospitalized lung cancer patients standardizes practices, reducing variability in management.

Indexed as

AlgorithmsCritical PathwaysImmune Checkpoint InhibitorsLung NeoplasmsPneumoniaAgedAged, 80 and overAntibodies, Monoclonal, HumanizedCarcinoma, Non-Small-Cell LungFemaleHospitalizationHumansMaleMiddle AgedAntibodies, Monoclonal, HumanizedImmune Checkpoint InhibitorsClinical care pathway algorithmImmune checkpoint inhibitor-related pneumonitisOnco-hospitalist

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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.