Evidence map›Paper›PMID 25810005›Full record

ArticleCancer medicine2015

Assessing patients' risk of febrile neutropenia: is there a correlation between physician-assessed risk and model-predicted risk?

Gary H Lyman, David C Dale, Jason C Legg, Esteban Abella, Phuong Khanh Morrow, Sadie Whittaker, Jeffrey Crawford

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in Cancer medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.0field-weighted citation impact, top 12% 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

10 citing papers in PubMed, 24 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Review
  4. Real-world evaluation of supportive care using an electronic health record text-mining tool: G-CSF use in breast cancer patients.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2022
    Article
  5. Article
  6. Article
  7. Article
  8. Use of prophylactic growth factors and antimicrobials in elderly patients with cancer: a review of the Medicare database.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2017
    Article
  9. Predicting neutropenia risk in patients with cancer using electronic data.Journal of the American Medical Informatics Association : JAMIA · 2017
    Article
  10. Article
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

7 authors at 4 institutions in 1 country.

Gary H LymanHutchinson Institute for Cancer Outcomes Research, Fred Hutchinson Cancer Research Center, Seattle, Washington.
David C DaleDepartment of Medicine, University of Washington, Seattle, Washington.
Jason C LeggGlobal Biostatistical Science, Amgen Inc., Thousand Oaks, California.
Esteban AbellaHematology/Oncology, Amgen Inc., Thousand Oaks, California.
Phuong Khanh MorrowHematology/Oncology, Amgen Inc., Thousand Oaks, California.
Sadie WhittakerHematology/Oncology, Amgen Inc., Thousand Oaks, California.
Jeffrey CrawfordDepartment of Medicine, Duke University School of Medicine and Duke Cancer Institute, Durham, North Carolina.
Amgen (United States) · USDuke University · USFred Hutch Cancer Center · USUniversity of Washington · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study evaluated the correlation between the risk of febrile neutropenia (FN) estimated by physicians and the risk of severe neutropenia or FN predicted by a validated multivariate model in patients with nonmyeloid malignancies receiving chemotherapy. Before patient enrollment, physician and site characteristics were recorded, and physicians self-reported the FN risk at which they would typically consider granulocyte colony-stimulating factor (G-CSF) primary prophylaxis (FN risk intervention threshold). For each patient, physicians electronically recorded their estimated FN risk, orders for G-CSF primary prophylaxis (yes/no), and patient characteristics for model predictions. Correlations between physician-assessed FN risk and model-predicted risk (primary endpoints) and between physician-assessed FN risk and G-CSF orders were calculated. Overall, 124 community-based oncologists registered; 944 patients initiating chemotherapy with intermediate FN risk enrolled. Median physician-assessed FN risk over all chemotherapy cycles was 20.0%, and median model-predicted risk was 17.9%; the correlation was 0.249 (95% CI, 0.179-0.316). The correlation between physician-assessed FN risk and subsequent orders for G-CSF primary prophylaxis (n = 634) was 0.313 (95% CI, 0.135-0.472). Among patients with a physician-assessed FN risk ≥ 20%, 14% did not receive G-CSF orders. G-CSF was not ordered for 16% of patients at or above their physician's self-reported FN risk intervention threshold (median, 20.0%) and was ordered for 21% below the threshold. Physician-assessed FN risk and model-predicted risk correlated weakly; however, there was moderate correlation between physician-assessed FN risk and orders for G-CSF primary prophylaxis. Further research and education on FN risk factors and appropriate G-CSF use are needed.

Indexed as

AdultAgedAged, 80 and overAntineoplastic Combined Chemotherapy ProtocolsComorbidityFebrile NeutropeniaFemaleGranulocyte Colony-Stimulating FactorHumansMaleMiddle AgedNeoplasmsNeoplasm StagingPhysiciansRiskUnited StatesGranulocyte Colony-Stimulating FactorChemotherapyfebrile neutropeniagranulocyte colony-stimulating factorneutropeniaprimary prophylaxisrisk assessmentrisk factorsrisk modelsevere neutropenia

Identifiers

PMID25810005
PMCPMC4559026
OpenAlexW2087440397

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.