Evidence map›Paper›PMID 39102887›Full record

ArticleJournal of the National Cancer Institute. Monographs2024

Toward real-time reporting of cancer incidence: methodology, pilot study, and SEER Program implementation.

Huann-Sheng Chen, Serban Negoita, Steve Schwartz, Elizabeth Hsu, Jennifer Hafterson, Linda Coyle, Jennifer Stevens, Anna Fernandez, Mary Potts, Eric J Feuer

Abstract read
In one paragraph

Article in Journal of the National Cancer Institute. Monographs, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Modeling Reporting Delay in Cancer Incidence Counts in the Evolving US and Canadian Population-Based Cancer Registry Environment.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025
    Article
  5. The SEER Program's evolution: supporting clinically meaningful population-level research.Journal of the National Cancer Institute. Monographs · 2024
    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.

Huann-Sheng ChenDivision of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD, USA.ORCID 0000-0002-5905-8050
Serban NegoitaDivision of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD, USA.ORCID 0000-0002-9327-9519
Steve SchwartzFred Hutch Cancer Surveillance System (CSS), Seattle, WA, USA.
Elizabeth HsuDivision of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD, USA.
Jennifer HaftersonFred Hutch Cancer Surveillance System (CSS), Seattle, WA, USA.ORCID 0009-0003-3410-2494
Linda CoyleInformation Management Services (IMS), Inc, Calverton, MD, USA.
Jennifer StevensInformation Management Services (IMS), Inc, Calverton, MD, USA.
Anna FernandezDivision of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD, USA.
Mary PottsFred Hutch Cancer Surveillance System (CSS), Seattle, WA, USA.
Eric J FeuerDivision of Cancer Control and Population Sciences, National Cancer Institute, Rockville, MD, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA lag time between cancer case diagnosis and incidence reporting impedes the ability to monitor the impact of recent events on cancer incidence. Currently, the data submission standard is 22 months after a diagnosis year ends, and the reporting standard is 27.5 months after a diagnosis year ends. This paper presents the National Cancer Institute (NCI) Surveillance, Epidemiology, and End Results (SEER) Program's efforts to minimize the lag and achieve "real-time" reporting, operationalized as submission within 2 months from the end of a diagnosis year.

methodsTechnology for rapidly creating a consolidated tumor case (CTC) from electronic pathology (e-path) reports is described. Statistical methods are extended to adjust for biases in incidence rates due to reporting delays for the most recent diagnosis years.

resultsA registry pilot study demonstrated that real-time submissions can approximate rates obtained from 22-month submissions after adjusting for reporting delays. A plan to be implemented across the SEER Program rapidly ascertains unstructured e-path reports and uses machine learning algorithms to translate the reports into the core data items that comprise a CTC for incidence reporting. Across the program, cases were submitted 2 months after the end of the calendar year. Registries with the most promising baseline values and a willingness to modify registry operations have joined a program to become certified as real-time reporting.

conclusionAdvances in electronic reporting, natural language processing, registry operations, and statistical methodology, energized by the SEER Program's mobilization and coordination of these efforts, will make real-time reporting an achievable goal.

Indexed as

NeoplasmsSEER ProgramHumansIncidenceNational Cancer Institute (U.S.)Pilot ProjectsRegistriesUnited States

Identifiers

PMID39102887
PMCPMC12104527

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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.