Evidence map›Paper›PMID 36865796›Full record

ArticleFrontiers in oncology2023

Comprehensive genomic profiling: Does timing matter?

Bicky Thapa, Gulrayz Ahmed, Aniko Szabo, Mandana Kamgar, Deepak Kilari, Maahum Mehdi, Smitha Menon, Sherin Daniel, Jonathan Thompson, James Thomas and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 14% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Observational
  6. Article
  7. Article
  8. 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

11 authors at 1 institution in 1 country.

Bicky ThapaDivision of Hematology and Oncology, Medical College of Wisconsin, Milwaukee, WI, United States.
Gulrayz AhmedDivision of Hematology and Oncology, Medical College of Wisconsin, Milwaukee, WI, United States.
Aniko SzaboDepartment of Biostatistics, Medical College of Wisconsin, Milwaukee, WI, United States.
Mandana KamgarDivision of Hematology and Oncology, Medical College of Wisconsin, Milwaukee, WI, United States.
Deepak KilariDivision of Hematology and Oncology, Medical College of Wisconsin, Milwaukee, WI, United States.
Maahum MehdiMedical School, Medical College of Wisconsin, Milwaukee, WI, United States.
Smitha MenonDivision of Hematology and Oncology, Medical College of Wisconsin, Milwaukee, WI, United States.
Sherin DanielDivision of Hematology and Oncology, Medical College of Wisconsin, Milwaukee, WI, United States.
Jonathan ThompsonDivision of Hematology and Oncology, Medical College of Wisconsin, Milwaukee, WI, United States.
James ThomasDivision of Hematology and Oncology, Medical College of Wisconsin, Milwaukee, WI, United States.
Ben GeorgeDivision of Hematology and Oncology, Medical College of Wisconsin, Milwaukee, WI, United States.
Medical College of Wisconsin · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: There is variability in utilization of Comprehensive Genomic Profiling (CGP) in most of the metastatic solid tumors (MST). We evaluated the CGP utilization patterns and its impact on outcomes at an academic tertiary center. Patients and Methods: Institutional database was reviewed for CGP data in adult patients with MST between 01/2012 - 04/2020. Patients were categorized based on interval between CGP and metastatic diagnosis; 3 tertiles of distribution (T1-earliest to the diagnosis, T3-furthest), and pre-mets (CGP performed prior to diagnosis of metastasis). Overall survival (OS) was estimated from the time of metastatic diagnosis with left truncation at the time of CGP. Cox regression model was used to estimate the impact of timing of CGP on survival. Results: Among 1,358 patients, 710 were female, 1,109 Caucasian, 186 Afro-Americans, and 36 Hispanic. The common histologies were lung cancer (254; 19%), colorectal cancer (203; 15%), gynecologic cancers (121; 8.9%), and pancreatic cancer (106; 7.8%). Time interval between diagnosis of metastatic disease and CGP was not statistically significantly different based on sex, race and ethnicity after adjusting for histologic diagnoses with 2 exceptions - Hispanics with lung cancer had delayed CGP compared to non-Hispanics (p =0.019) and females with pancreas cancer had delayed CGP compared to males (p =0.025). Lung cancer, gastro-esophageal cancer and gynecologic malignancies had better survival if they had CGP performed during the first tertile after metastatic diagnosis. Conclusion: CGP utilization across cancer types was equitable irrespective of sex, race and ethnicity. Early CGP after metastatic diagnosis might have effect on treatment delivery and clinical outcomes in cancer type with more actionable targets.

Indexed as

best practicecomprehensive genomic profilingdisparitiesmetastatic solid tumorsprecision oncology

Identifiers

PMID36865796
PMCPMC9971445
OpenAlexW4320723980

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.