Evidence map›Paper›PMID 27939002›Full record

ArticleOral oncology2016

Individualized risk prediction of outcomes for oral cavity cancer patients.

Victoria Prince, Emily L Bellile, Yilun Sun, Gregory T Wolf, Connor W Hoban, Andrew G Shuman, Jeremy M G Taylor

Abstract read
In one paragraph

Article in Oral oncology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

7 authors.

Victoria PrinceDepartment of Otolaryngology, University of Michigan, Ann Arbor, MI 48109, United States.
Emily L BellileDepartment of Biostatistics, University of Michigan, Ann Arbor, MI 48109, United States.
Yilun SunDepartment of Biostatistics, University of Michigan, Ann Arbor, MI 48109, United States.
Gregory T WolfDepartment of Otolaryngology, University of Michigan, Ann Arbor, MI 48109, United States.
Connor W HobanDepartment of Otolaryngology, University of Michigan, Ann Arbor, MI 48109, United States.
Andrew G ShumanDepartment of Otolaryngology, University of Michigan, Ann Arbor, MI 48109, United States.
Jeremy M G TaylorDepartment of Biostatistics, University of Michigan, Ann Arbor, MI 48109, United States. Electronic address: jmgt@umich.edu.

Funding

XenograftP30CA046592 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Eric R. Fearon · 1988 to 2026
$178.2M
Therapeutic Potential and Mechanism of Action of Potent Small Molecule InhibitorsP50CA097248 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI NOR, JACQUES EDUARDO · 2002 to 2013
$25.3M
Statistical Methods for Cancer BiomarkersR01CA129102 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GHOSH, DEBASHIS, TAYLOR, JEREMY M.G. · 2009 to 2021
$3.3M
NCI NIH HHS P30 CA046592NCI NIH HHS P50 CA097248NCI NIH HHS R01 CA129102
6 · The paper itself

Abstract

backgroundOptimal management of oral cancer relies upon accurate and individualized risk prediction of relevant clinical outcomes. Individualized prognostic calculators have been developed to guide patient-physician communication and treatment-related decision-making. However it is critical to scrutinize their accuracy prior to integrating into clinical care.

aimTo compare and evaluate oral cavity cancer prognostic calculators using an independent dataset.

methodsFive prognostic calculators incorporating patient and tumor characteristics were identified that evaluated five-year overall survival. A total of 505 patients with previously untreated oral cancer diagnosed between 2003 and 2014 were analyzed. Calculators were applied to each patient to generate individual predicted survival probabilities. Predictions were compared among prognostic tools and with observed outcomes using Kaplan-Meier plots, ROC curves and calibration plots.

resultsCorrelation between the five calculators varied from 0.59 to 0.86. There were considerable differences between individual predictions from pairs of calculators, with as many as 64% of patients having predictions that differed by more than 10%. Four of five calculators were well calibrated. For all calculators the predictions were associated with survival outcomes. The area under the ROC curve ranged from 0.65 to 0.71, with C-indices ranging from 0.63 to 0.67. An average of the 5 predictions had slightly better performance than any individual calculator.

conclusionFive prognostic calculators designed to predict individual outcomes of oral cancer differed significantly in their assessments of risk. Most were well calibrated and had modest discriminatory ability. Given the increasing importance of individualized risk prediction, more robust models are needed.

Indexed as

AdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedMouth NeoplasmsRisk AssessmentTreatment OutcomeCalculatorCalibrationDiscriminationNomogramOral cavityOverall survivalRisk prediction

Identifiers

PMID27939002
PMCPMC5193389

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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.