Evidence map›Paper›PMID 29700384›Full record

ArticleScientific reports2018

A Temporal Examination of Platelet Counts as a Predictor of Prognosis in Lung, Prostate, and Colon Cancer Patients.

Joanna L Sylman, Hunter B Boyce, Annachiara Mitrugno, Garth W Tormoen, I-Chun Thomas, Todd H Wagner, Jennifer S Lee, John T Leppert, Owen J T McCarty, Parag Mallick

Abstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

  1. Review
  2. Article
  3. Targeting platelet-tumor cell interactions: a novel approach to cancer therapy.Medical oncology (Northwood, London, England) · 2025
    Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. Article
  11. mCRPC Patients ReceivingJournal of nuclear medicine : official publication, Society of Nuclear Medicine · 2022
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. 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

10 authors.

Joanna L SylmanBiomedical Engineering, School of Medicine, Oregon Health and Science University, Portland, OR, USA. jsylman@gmail.com.
Hunter B BoyceCanary Center at Stanford, Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA.
Annachiara MitrugnoBiomedical Engineering, School of Medicine, Oregon Health and Science University, Portland, OR, USA.
Garth W TormoenDepartment of Radiation Medicine, Oregon Health & Science University, 3181 SW, Sam Jackson Park Rd, Portland, OR, USA.
I-Chun ThomasVA Palo Alto Health Care System, Palo Alto, CA, USA.
Todd H WagnerVA Palo Alto Health Care System, Palo Alto, CA, USA.
Jennifer S LeeVA Palo Alto Health Care System, Palo Alto, CA, USA.
John T LeppertVA Palo Alto Health Care System, Palo Alto, CA, USA.
Owen J T McCartyBiomedical Engineering, School of Medicine, Oregon Health and Science University, Portland, OR, USA.
Parag MallickCanary Center at Stanford, Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA.

Funding

POSTDOCTORAL TRAINING IN MEDICAL INFORMATION SCIENCEST15LM007033 · NLM · STANFORD UNIVERSITY · PI SYLVIA KATINA PLEVRITIS · 1985 to 2026
$25.5M
Characterization of Coagulation Factor-platelet Interactions: Role of FXIR01HL101972 · NHLBI · OREGON HEALTH & SCIENCE UNIVERSITY · PI Owen J McCarty · 2010 to 2026
$8.5M
NHLBI NIH HHS R01 HL101972NLM NIH HHS T15 LM007033
6 · The paper itself

Abstract

Platelets, components of hemostasis, when present in excess (>400 K/μL, thrombocytosis) have also been associated with worse outcomes in lung, ovarian, breast, renal, and colorectal cancer patients. Associations between thrombocytosis and cancer outcomes have been made mostly from single-time-point studies, often at the time of diagnosis. Using laboratory data from the Department of Veterans Affairs (VA), we examined the potential benefits of using longitudinal platelet counts in improving patient prognosis predictions. Ten features (summary statistics and engineered features) were derived to describe the platelet counts of 10,000+ VA lung, prostate, and colon cancer patients and incorporated into an age-adjusted LASSO regression analysis to determine feature importance, and predict overall or relapse-free survival, which was compared to the previously used approach of monitoring for thrombocytosis near diagnosis (Postdiag AG400 model). Temporal features describing acute platelet count increases/decreases were found to be important in cancer survival and relapse-survival that helped stratify good and bad outcomes of cancer patient groups. Predictions of overall and relapse-free survival were improved by up to 30% compared to the Postdiag AG400 model. Our study indicates the association of temporally derived platelet count features with a patients' prognosis predictions.

Indexed as

Platelet CountAdultAgedBiomarkersColonic NeoplasmsComorbidityHumansKaplan-Meier EstimateLung NeoplasmsMaleMiddle AgedNeoplasm StagingOdds RatioPrognosisProstatic NeoplasmsRetrospective StudiesBiomarkers

Identifiers

PMID29700384
PMCPMC5920102

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Registered trials

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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.