Evidence map›Paper›PMID 35264135›Full record

ArticleBMC cancer2022

Trends in treatment patterns and survival outcomes in advanced non-small cell lung cancer: a Canadian population-based real-world analysis.

Robert Carroll, Margherita Bortolini, Alan Calleja, Robin Munro, Shiying Kong, Melinda J Daumont, John R Penrod, Khalid Lakhdari, Laure Lacoin, Winson Y Cheung

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
4.3field-weighted citation impact, top 5% of its field
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

23 citing papers in PubMed, 27 citations in OpenAlex.

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  14. Real-World Evidence Study of Patients withCurrent oncology (Toronto, Ont.) · 2024
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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

10 authors at 6 institutions in 4 countries.

Robert CarrollCentre for Observational Research & Data Sciences, Bristol Myers Squibb, Uxbridge, UK.
Margherita BortoliniReal World Solutions, IQVIA, London, UK.
Alan CallejaReal World Solutions, IQVIA, London, UK.
Robin MunroReal World Solutions, IQVIA, London, UK.
Shiying KongDepartment of Oncology, University of Calgary, Calgary, AB, Canada.
Melinda J DaumontWorldwide Health Economics & Outcomes Research, Bristol Myers Squibb, Braine-l'Alleud, Belgium.
John R PenrodWorldwide Health Economics & Outcomes Research, Bristol Myers Squibb, Princeton, NJ, USA.
Khalid LakhdariHealth Economics and Market Access Oncology, Bristol Myers Squibb, Saint-Laurent, QC, Canada.
Laure LacoinEpi-Fit, Bordeaux, Nouvelle-Aquitaine, France.
Winson Y CheungDepartment of Medical Oncology, Tom Baker Cancer Centre, University of Calgary, Calgary, AB, Canada. winson.cheung@ahs.ca.
IQVIA (United Kingdom) · GBUniversity of Calgary · CABristol-Myers Squibb (Belgium) · BEBristol-Myers Squibb (Canada) · CABristol-Myers Squibb (United Kingdom) · GBBristol-Myers Squibb (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs part of the multi-country I-O Optimise research initiative, this population-based study evaluated real-world treatment patterns and overall survival (OS) in patients treated for advanced non-small cell lung cancer (NSCLC) before and after public reimbursement of immuno-oncology (I-O) therapies in Alberta province, Canada.

methodsThis study used data from the Oncology Outcomes (O2) database, which holds information for ~ 4.5 million residents of Alberta. Eligible patients were adults newly diagnosed with NSCLC between January 2010 and December 2017 and receiving first-line therapy for advanced NSCLC (stage IIIB or IV) either in January 2010-March 2016 (pre-I-O period) or April 2016-June 2019 (post-I-O period). Time periods were based on the first public reimbursement of I-O therapy in Alberta (April 2017), with a built-in 1-year lag time before this date to allow progression to second-line therapy, for which the I-O therapy was indicated. Kaplan-Meier methods were used to estimate OS.

resultsOf 2244 analyzed patients, 1501 (66.9%) and 743 (33.1%) received first-line treatment in the pre-I-O and post-I-O periods, respectively. Between the pre-I-O and post-I-O periods, proportions of patients receiving chemotherapy decreased, with parallel increases in proportions receiving I-O therapies in both the first-line (from < 0.5% to 17%) and second-line (from 8% to 47%) settings. Increased use of I-O therapies in the post-I-O period was observed in subgroups with non-squamous (first line, 15%; second line, 39%) and squamous (first line, 25%; second line, 65%) histology. First-line use of tyrosine kinase inhibitors also increased among patients with non-squamous histology (from 26% to 30%). In parallel with these evolving treatment patterns, median OS increased from 10.2 to 12.1 months for all patients (P < 0.001), from 11.8 to 13.7 months for patients with non-squamous histology (P = 0.022) and from 7.8 to 9.4 months for patients with squamous histology (P = 0.215).

conclusionsFollowing public reimbursement, there was a rapid and profound adoption of I-O therapies for advanced NSCLC in Alberta, Canada. In addition, OS outcomes were significantly improved for patients treated in the post-I-O versus pre-I-O periods. These data lend support to the emerging body of evidence for the potential real-world benefits of I-O therapies for treatment of patients with advanced NSCLC.

Indexed as

AdultAgedAged, 80 and overAlbertaCarcinoma, Non-Small-Cell LungFemaleHumansImmunotherapyInsurance, Health, ReimbursementLung NeoplasmsMaleMedical OncologyMiddle AgedPractice Patterns, Physicians'Immune checkpoint inhibitorsImmunotherapyNon-small cell lung cancerPopulation basedReal-world evidenceRetrospective cohort studySurvivalTreatment patterns

Identifiers

PMID35264135
PMCPMC8908553
OpenAlexW4220990951

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.