Evidence map›Paper›PMID 31910880›Full record

ArticleJournal of translational medicine2020

Multi-omic serum biomarkers for prognosis of disease progression in prostate cancer.

Michael A Kiebish, Jennifer Cullen, Prachi Mishra, Amina Ali, Eric Milliman, Leonardo O Rodrigues, Emily Y Chen, Vladimir Tolstikov, Lixia Zhang, Kiki Panagopoulos and 13 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 1 pooled it
–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

38 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  13. Prostate cancer theragnostics biomarkers: An update.Investigative and clinical urology · 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

23 authors.

Michael A KiebishBERG LLC, Framingham, MA, USA.
Jennifer CullenHenry Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA.
Prachi MishraHenry Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA.
Amina AliCenter for Prostate Disease Research, Department of Surgery, Uniformed Services University and the Walter Reed National Military Medical Center, Bethesda, MD, USA.
Eric MillimanBERG LLC, Framingham, MA, USA.
Leonardo O RodriguesBERG LLC, Framingham, MA, USA.
Emily Y ChenBERG LLC, Framingham, MA, USA.
Vladimir TolstikovBERG LLC, Framingham, MA, USA.
Lixia ZhangBERG LLC, Framingham, MA, USA.
Kiki PanagopoulosBERG LLC, Framingham, MA, USA.
Punit ShahBERG LLC, Framingham, MA, USA.
Yongmei ChenHenry Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA.
Gyorgy PetrovicsHenry Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA.
Inger L RosnerCenter for Prostate Disease Research, Department of Surgery, Uniformed Services University and the Walter Reed National Military Medical Center, Bethesda, MD, USA.
Isabell A SesterhennJoint Pathology Center, Silver Spring, MD, USA.
David G McLeodCenter for Prostate Disease Research, Department of Surgery, Uniformed Services University and the Walter Reed National Military Medical Center, Bethesda, MD, USA.
Elder GrangerBERG LLC, Framingham, MA, USA.
Rangaprasad SarangarajanBERG LLC, Framingham, MA, USA.
Viatcheslav AkmaevBERG LLC, Framingham, MA, USA.
Alagarsamy SrinivasanHenry Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA.
Shiv SrivastavaCenter for Prostate Disease Research, Department of Surgery, Uniformed Services University and the Walter Reed National Military Medical Center, Bethesda, MD, USA.
Niven R NarainBERG LLC, Framingham, MA, USA.
Albert DobiHenry Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA. adobi@cpdr.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPredicting the clinical course of prostate cancer is challenging due to the wide biological spectrum of the disease. The objective of our study was to identify prostate cancer prognostic markers in patients 'sera using a multi-omics discovery platform.

methodsPre-surgical serum samples collected from a longitudinal, racially diverse, prostate cancer patient cohort (N = 382) were examined. Linear Regression and Bayesian computational approaches integrated with multi-omics, were used to select markers to predict biochemical recurrence (BCR). BCR-free survival was modeled using unadjusted Kaplan-Meier estimation curves and multivariable Cox proportional hazards analysis, adjusted for key pathologic variables. Receiver operating characteristic (ROC) curve statistics were used to examine the predictive value of markers in discriminating BCR events from non-events. The findings were further validated by creating a training set (N = 267) and testing set (N = 115) from the cohort.

resultsAmong 382 patients, 72 (19%) experienced a BCR event in a median follow-up time of 6.9 years. Two proteins-Tenascin C (TNC) and Apolipoprotein A1V (Apo-AIV), one metabolite-1-Methyladenosine (1-MA) and one phospholipid molecular species phosphatidic acid (PA) 18:0-22:0 showed a cumulative predictive performance of AUC = 0.78 [OR (95% CI) = 6.56 (2.98-14.40), P < 0.05], in differentiating patients with and without BCR event. In the validation set all four metabolites consistently reproduced an equivalent performance with high negative predictive value (NPV; > 80%) for BCR. The combination of pTstage and Gleason score with the analytes, further increased the sensitivity [AUC = 0.89, 95% (CI) = 4.45-32.05, P < 0.05], with an increased NPV (0.96) and OR (12.4) for BCR. The panel of markers combined with the pathological parameters demonstrated a more accurate prediction of BCR than the pathological parameters alone in prostate cancer.

conclusionsIn this study, a panel of serum analytes were identified that complemented pathologic patient features in predicting prostate cancer progression. This panel offers a new opportunity to complement current prognostic markers and to monitor the potential impact of primary treatment versus surveillance on patient oncological outcome.

Indexed as

ProstatectomyProstatic NeoplasmsBayes TheoremBiomarkersDisease ProgressionHumansMaleNeoplasm GradingNeoplasm Recurrence, LocalPrognosisProstate-Specific AntigenBiomarkersProstate-Specific AntigenBayesian networksBiochemical recurrenceBiomarkersMetabolomicsProstate cancer

Identifiers

PMID31910880
PMCPMC6945688

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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.