Evidence map›Paper›PMID 33116902›Full record

ArticleClinical epidemiology2020

Validation of an Algorithm to Ascertain Late Breast Cancer Recurrence Using Danish Medical Registries.

Rikke Nørgaard Pedersen, Buket Öztürk, Lene Mellemkjær, Søren Friis, Trine Tramm, Mette Nørgaard, Deirdre P Cronin-Fenton

Abstract read
In one paragraph

Article in Clinical epidemiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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  6. Evaluation of Algorithms Using Automated Health Plan Data to Identify Breast Cancer Recurrences.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 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

7 authors.

Rikke Nørgaard PedersenDepartment of Clinical Epidemiology, Aarhus University, Aarhus, Denmark.ORCID 0000-0002-7437-174X
Buket ÖztürkDepartment of Clinical Epidemiology, Aarhus University, Aarhus, Denmark.ORCID 0000-0003-2957-7797
Lene MellemkjærDanish Cancer Society Research Center, Copenhagen, Denmark.ORCID 0000-0001-9222-6215
Søren FriisDanish Cancer Society Research Center, Copenhagen, Denmark.
Trine TrammDepartment of Pathology, Aarhus University Hospital, Aarhus, Denmark.ORCID 0000-0003-3894-4552
Mette NørgaardDepartment of Clinical Epidemiology, Aarhus University, Aarhus, Denmark.ORCID 0000-0001-6110-5891
Deirdre P Cronin-FentonDepartment of Clinical Epidemiology, Aarhus University, Aarhus, Denmark.ORCID 0000-0001-9738-2284

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeAbout 70% of women with breast cancer survive at least 10 years after diagnosis. We constructed an algorithm to ascertain late breast cancer recurrence-which we define as breast cancer that recurs 10 years or more after primary diagnosis (excluding contralateral breast cancers)-using Danish nationwide medical registries. We used clinical information recorded in medical records as a reference standard.

methodsUsing the Danish Breast Cancer Group clinical database, we ascertained data on 21,134 women who survived recurrence-free 10 years or more after incident stage I-III breast cancer diagnosed in 1987-2004. We used a combination of Danish registries to construct the algorithm-the Danish National Patient Registry for information on diagnostic, therapeutic and procedural codes; and cancer diagnoses from the Danish Pathology Registry, the Danish Cancer Registry and the Contralateral Breast Cancer database. To estimate the positive predictive value (PPV), we selected 105 patients who, according to our algorithm, had late recurrence diagnosed at Aarhus University Hospital. To estimate the sensitivity, specificity and negative predictive value (NPV), we selected 114 patients diagnosed with primary breast cancer at Aalborg University Hospital. We abstracted clinical information on late recurrence for patients with medical record-confirmed late recurrence at Aarhus University Hospital.

resultsOur algorithm had a PPV of late recurrence of 85.7% (95% CI: 77.5-91.3%), a sensitivity of 100.0% (95% CI, 39.8-100.0%), a specificity of 97.3 (95% CI, 92.2-99.4) and a NPV of 100% (95% CI, 96.6-100.0%).

conclusionOur algorithm for late recurrence showed a moderate to high PPV and high sensitivity, specificity and negative predictive value. The algorithm could be an important tool for future studies of late breast cancer recurrence.

Indexed as

algorithmbreast cancer neoplasmlate breast cancer recurrencePPVsensitivity

Identifiers

PMID33116902
PMCPMC7569071

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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.