Evidence map›Paper›PMID 25417240›Full record

ArticleJournal of the National Cancer Institute. Monographs2014

The Surveillance, Epidemiology, and End Results Cancer Survival Calculator SEER*CSC: validation in a managed care setting.

Eric J Feuer, Borsika A Rabin, Zhaohui Zou, Zhuoqiao Wang, Xiaoqin Xiong, Jennifer L Ellis, John F Steiner, Laurie Cynkin, Larissa Nekhlyudov, Elizabeth Bayliss and 1 more

Abstract readValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the National Cancer Institute. Monographs, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 2 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

14 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Improved breast lesion detection in mammogram images using a deep neural network.Diagnostic and interventional radiology (Ankara, Turkey) · 2023
    Article
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  10. Review
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  12. Cancer survival: an overview of measures, uses, and interpretation.Journal of the National Cancer Institute. Monographs · 2014
    Article
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  14. 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

11 authors.

Eric J FeuerDivision of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD (EJF, LC); Cancer Research Network Cancer Communication Research Center (BAR); and Institute for Health Research (JLE, JFS), Kaiser Permanente Colorado, Denver, CO; Information Management Services, Inc., Calverton, MD (ZZ, ZW, XX); Department of Family Medicine, University of Colorado School of Medicine, Denver, CO (EB); Department of Population Medicine, Harvard Medical School, Boston, MA (LN); CANSTAT, Plano, TX (BFH).
Borsika A RabinDivision of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD (EJF, LC); Cancer Research Network Cancer Communication Research Center (BAR); and Institute for Health Research (JLE, JFS), Kaiser Permanente Colorado, Denver, CO; Information Management Services, Inc., Calverton, MD (ZZ, ZW, XX); Department of Family Medicine, University of Colorado School of Medicine, Denver, CO (EB); Department of Population Medicine, Harvard Medical School, Boston, MA (LN); CANSTAT, Plano, TX (BFH).
Zhaohui ZouDivision of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD (EJF, LC); Cancer Research Network Cancer Communication Research Center (BAR); and Institute for Health Research (JLE, JFS), Kaiser Permanente Colorado, Denver, CO; Information Management Services, Inc., Calverton, MD (ZZ, ZW, XX); Department of Family Medicine, University of Colorado School of Medicine, Denver, CO (EB); Department of Population Medicine, Harvard Medical School, Boston, MA (LN); CANSTAT, Plano, TX (BFH).
Zhuoqiao WangDivision of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD (EJF, LC); Cancer Research Network Cancer Communication Research Center (BAR); and Institute for Health Research (JLE, JFS), Kaiser Permanente Colorado, Denver, CO; Information Management Services, Inc., Calverton, MD (ZZ, ZW, XX); Department of Family Medicine, University of Colorado School of Medicine, Denver, CO (EB); Department of Population Medicine, Harvard Medical School, Boston, MA (LN); CANSTAT, Plano, TX (BFH).
Xiaoqin XiongDivision of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD (EJF, LC); Cancer Research Network Cancer Communication Research Center (BAR); and Institute for Health Research (JLE, JFS), Kaiser Permanente Colorado, Denver, CO; Information Management Services, Inc., Calverton, MD (ZZ, ZW, XX); Department of Family Medicine, University of Colorado School of Medicine, Denver, CO (EB); Department of Population Medicine, Harvard Medical School, Boston, MA (LN); CANSTAT, Plano, TX (BFH).
Jennifer L EllisDivision of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD (EJF, LC); Cancer Research Network Cancer Communication Research Center (BAR); and Institute for Health Research (JLE, JFS), Kaiser Permanente Colorado, Denver, CO; Information Management Services, Inc., Calverton, MD (ZZ, ZW, XX); Department of Family Medicine, University of Colorado School of Medicine, Denver, CO (EB); Department of Population Medicine, Harvard Medical School, Boston, MA (LN); CANSTAT, Plano, TX (BFH).
John F SteinerDivision of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD (EJF, LC); Cancer Research Network Cancer Communication Research Center (BAR); and Institute for Health Research (JLE, JFS), Kaiser Permanente Colorado, Denver, CO; Information Management Services, Inc., Calverton, MD (ZZ, ZW, XX); Department of Family Medicine, University of Colorado School of Medicine, Denver, CO (EB); Department of Population Medicine, Harvard Medical School, Boston, MA (LN); CANSTAT, Plano, TX (BFH).
Laurie CynkinDivision of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD (EJF, LC); Cancer Research Network Cancer Communication Research Center (BAR); and Institute for Health Research (JLE, JFS), Kaiser Permanente Colorado, Denver, CO; Information Management Services, Inc., Calverton, MD (ZZ, ZW, XX); Department of Family Medicine, University of Colorado School of Medicine, Denver, CO (EB); Department of Population Medicine, Harvard Medical School, Boston, MA (LN); CANSTAT, Plano, TX (BFH).
Larissa NekhlyudovDivision of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD (EJF, LC); Cancer Research Network Cancer Communication Research Center (BAR); and Institute for Health Research (JLE, JFS), Kaiser Permanente Colorado, Denver, CO; Information Management Services, Inc., Calverton, MD (ZZ, ZW, XX); Department of Family Medicine, University of Colorado School of Medicine, Denver, CO (EB); Department of Population Medicine, Harvard Medical School, Boston, MA (LN); CANSTAT, Plano, TX (BFH).
Elizabeth BaylissDivision of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD (EJF, LC); Cancer Research Network Cancer Communication Research Center (BAR); and Institute for Health Research (JLE, JFS), Kaiser Permanente Colorado, Denver, CO; Information Management Services, Inc., Calverton, MD (ZZ, ZW, XX); Department of Family Medicine, University of Colorado School of Medicine, Denver, CO (EB); Department of Population Medicine, Harvard Medical School, Boston, MA (LN); CANSTAT, Plano, TX (BFH).
Benjamin F HankeyDivision of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD (EJF, LC); Cancer Research Network Cancer Communication Research Center (BAR); and Institute for Health Research (JLE, JFS), Kaiser Permanente Colorado, Denver, CO; Information Management Services, Inc., Calverton, MD (ZZ, ZW, XX); Department of Family Medicine, University of Colorado School of Medicine, Denver, CO (EB); Department of Population Medicine, Harvard Medical School, Boston, MA (LN); CANSTAT, Plano, TX (BFH). bhankey0411@aol.com.

Funding

Determining Processes of Cardiovascular Care Relevant to Complex PatientsR21HS019520 · AHRQ · KAISER FOUNDATION RESEARCH INSTITUTE · PI BAYLISS, ELIZABETH A · 2010 to 2010
$462k
AHRQ HHS R21HS019520PHS HHS HHSN261201300467P
6 · The paper itself

Abstract

backgroundNomograms for prostate and colorectal cancer are included in the Surveillance, Epidemiology, and End Results (SEER) Cancer Survival Calculator, under development by the National Cancer Institute. They are based on the National Cancer Institute's SEER data, coupled with Medicare data, to estimate the probabilities of surviving or dying from cancer or from other causes based on a set of patient and tumor characteristics. The nomograms provide estimates of survival that are specific to the characteristics of the tumor, age, race, gender, and the overall health of a patient. These nomograms have been internally validated using the SEER data. In this paper, we externally validate the nomograms using data from Kaiser Permanente Colorado.

methodsThe SEER Cancer Survival Calculator was externally validated using time-dependent area under the Receiver Operating Characteristic curve statistics and calibration plots for retrospective cohorts of 1102 prostate cancer and 990 colorectal cancer patients from Kaiser Permanente Colorado.

resultsThe time-dependent area under the Receiver Operating Characteristic curve statistics were computed for one, three, five, seven, and 10 year(s) postdiagnosis for prostate and colorectal cancer and ranged from 0.77 to 0.89 for death from cancer and from 0.72 to 0.81 for death from other causes. The calibration plots indicated a very good fit of the model for death from cancer for colorectal cancer and for the higher risk group for prostate cancer. For the lower risk groups for prostate cancer (<10% chance of dying of prostate cancer in 10 years), the model predicted slightly worse prognosis than observed. Except for the lowest risk group for colorectal cancer, the models for death from other causes for both prostate and colorectal cancer predicted slightly worse prognosis than observed.

conclusionsThe results of the external validation indicated that the colorectal and prostate cancer nomograms are reliable tools for physicians and patients to use to obtain information on prognosis and assist in establishing priorities for both treatment of the cancer and other conditions, particularly when a patient is elderly and/or has significant comorbidities. The slightly better than predicted risk of death from other causes in a health maintenance organization (HMO) setting may be due to an overall healthier population and the integrated management of disease relative to the overall population (as represented by SEER).

Indexed as

NomogramsColorectal NeoplasmsHumansMaleManaged Care ProgramsNeoplasmsPrognosisProstatic NeoplasmsRetrospective StudiesROC CurveSEER ProgramSurvival RateUnited States

Identifiers

PMID25417240
PMCPMC4841169

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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.