Evidence map›Paper›PMID 38696168›Full record

ArticleJAMA network open2024

Treatment Patterns and Attrition With Lines of Therapy for Advanced Urothelial Carcinoma in the US.

Vinay Mathew Thomas, Yeonjung Jo, Nishita Tripathi, Soumyajit Roy, Beverly Chigarira, Arshit Narang, Georges Gebrael, Chadi Hage Chehade, Nicolas Sayegh, Gliceida Galarza Fortuna and 6 more

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 2 pooled it
12.6field-weighted citation impact, top 1% 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

18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 22 citations in OpenAlex.

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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

16 authors at 6 institutions in 1 country.

Vinay Mathew ThomasDivision of Medical Oncology, Department of Internal Medicine, Huntsman Cancer Institute, University of Utah, Salt Lake City.
Yeonjung JoDivision of Medical Oncology, Department of Internal Medicine, Huntsman Cancer Institute, University of Utah, Salt Lake City.
Nishita TripathiDepartment of Internal Medicine, Detroit Medical Center Sinai Grace Hospital, Detroit, Michigan.
Soumyajit RoyDepartment of Radiation Oncology, Rush Cancer Center, Chicago, Illinois.
Beverly ChigariraDivision of Medical Oncology, Department of Internal Medicine, Huntsman Cancer Institute, University of Utah, Salt Lake City.
Arshit NarangDivision of Medical Oncology, Department of Internal Medicine, Huntsman Cancer Institute, University of Utah, Salt Lake City.
Georges GebraelDivision of Medical Oncology, Department of Internal Medicine, Huntsman Cancer Institute, University of Utah, Salt Lake City.
Chadi Hage ChehadeDivision of Medical Oncology, Department of Internal Medicine, Huntsman Cancer Institute, University of Utah, Salt Lake City.
Nicolas SayeghDepartment of Internal Medicine, University of Texas Southwestern Medical Center, Dallas.
Gliceida Galarza FortunaDivision of Medical Oncology, Department of Internal Medicine, Huntsman Cancer Institute, University of Utah, Salt Lake City.
Richard JiDivision of Medical Oncology, Department of Internal Medicine, Huntsman Cancer Institute, University of Utah, Salt Lake City.
Patrick CampbellDivision of Medical Oncology, Department of Internal Medicine, Huntsman Cancer Institute, University of Utah, Salt Lake City.
Haoran LiDivision of Medical Oncology, Department of Internal Medicine, University of Kansas Cancer Center, Westwood.
Neeraj AgarwalDivision of Medical Oncology, Department of Internal Medicine, Huntsman Cancer Institute, University of Utah, Salt Lake City.
Sumati GuptaDivision of Medical Oncology, Department of Internal Medicine, Huntsman Cancer Institute, University of Utah, Salt Lake City.
Umang SwamiDivision of Medical Oncology, Department of Internal Medicine, Huntsman Cancer Institute, University of Utah, Salt Lake City.
Huntsman Cancer Institute · USUniversity of Utah · USRush University · USSinai Grace Hospital · USThe University of Kansas Cancer Center · USThe University of Texas Southwestern Medical Center · US

Funding

UTAH REGIONAL CANCER CENTERP30CA042014 · NCI · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Jared P Rutter · 1986 to 2026
$72.6M
NCI NIH HHS P30 CA042014
6 · The paper itself

Abstract

Importance: The treatment paradigm for advanced urothelial carcinoma (aUC) has undergone substantial transformation due to the introduction of effective, novel therapeutic agents. However, outcomes remain poor, and little is known about current treatment approaches and attrition rates for patients with aUC. Objectives: To delineate evolving treatment patterns and attrition rates in patients with aUC using a US-based patient-level sample. Design, Setting, and Participants: This retrospective cohort study used patient-level data from the nationwide deidentified electronic health record database Flatiron Health, originating from approximately 280 oncology clinics across the US. Patients included in the analysis received treatment for metastatic or local aUC at a participating site from January 1, 2011, to January 31, 2023. Patients receiving treatment for 2 or more different types of cancer or participating in clinical trials were excluded from the analysis. Main Outcomes and Measures: Frequencies and percentages were used to summarize the (1) treatment received in each line (cisplatin-based regimens, carboplatin-based regimens, programmed cell death 1 and/or programmed cell death ligand 1 [PD-1/PD-L1] inhibitors, single-agent nonplatinum chemotherapy, enfortumab vedotin, erdafitinib, sacituzumab govitecan, or others) and (2) attrition of patients with each line of therapy, defined as the percentage of patients not progressing to the next line. Results: Of the 12 157 patients within the dataset, 7260 met the eligibility criteria and were included in the analysis (5364 [73.9%] men; median age at the start of first-line treatment, 73 [IQR, 66-80] years). All patients commenced first-line treatment; of these, only 2714 (37.4%) progressed to receive second-line treatment, and 857 (11.8%) advanced to third-line treatment. The primary regimens used as first-line treatment contained carboplatin (2241 [30.9%]), followed by PD-1/PD-L1 inhibitors (2174 [29.9%]). The PD-1/PD-L1 inhibitors emerged as the predominant choice in the second- and third-line (1412 of 2714 [52.0%] and 258 of 857 [30.1%], respectively) treatments. From 2019 onward, novel therapeutic agents were increasingly used in second- and third-line treatments, including enfortumab vedotin (219 of 2714 [8.1%] and 159 of 857 [18.6%], respectively), erdafitinib (39 of 2714 [1.4%] and 28 of 857 [3.3%], respectively), and sacituzumab govitecan (14 of 2714 [0.5%] and 34 of 857 [4.0%], respectively). Conclusions and Relevance: The findings of this cohort study suggest that approximately two-thirds of patients with aUC did not receive second-line treatment. Most first-line treatments do not include cisplatin-based regimens and instead incorporate carboplatin- or PD-1/PD-L1 inhibitor-based therapies. These data warrant the provision of more effective and tolerable first-line treatments for patients with aUC.

Indexed as

CarboplatinAgedAged, 80 and overAntibodies, MonoclonalAntineoplastic AgentsAntineoplastic Combined Chemotherapy ProtocolsCarcinoma, Transitional CellCisplatinFemaleHumansImmune Checkpoint InhibitorsMaleMiddle AgedRetrospective StudiesUnited StatesUrinary Bladder NeoplasmsAntibodies, MonoclonalAntineoplastic AgentsCarboplatinCisplatinenfortumab vedotinImmune Checkpoint Inhibitors

Identifiers

PMID38696168
PMCPMC11066705
OpenAlexW4396577541

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.