Evidence map›Paper›PMID 33398646›Full record

ReviewAnnals of surgical oncology2021

Personalized Screening for Breast Cancer: Rationale, Present Practices, and Future Directions.

Tanir M Allweis, Naama Hermann, Rinat Berenstein-Molho, Michal Guindy

Abstract readReview
PubMed Publisher
In one paragraph

Review in Annals of surgical oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

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

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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

4 authors.

Tanir M Allweis *Department of Surgery and Breast Health Center, Kaplan Medical Center, Rehovot, Israel. tanirallwis@gmail.com.ORCID http://orcid.org/0000-0002-1693-7012
Naama Hermann *Department of General Surgery B and Meirav Comprehensive Breast Health Center, Sheba Medical Center, Ramat Gan, Israel.
Rinat Berenstein-MolhoBreast Cancer Unit, Oncology Institute, Chaim Sheba Medical Center, Tel-Hashomer, Israel.
Michal GuindyDepartment of Imaging, Assuta Medical Center, Tel Aviv, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ever since screening for early breast cancer (BC) diagnosis was shown to decrease mortality from the disease, screening programs have been widely implemented throughout the world. Targeted age groups and schedules vary between countries but the majority use a population-based approach, regardless of personal BC risk. The purpose of this review was to describe current population-based screening practices, point out some of the shortcomings of these practices, describe BC risk factors and risk assessment models, and present ongoing clinical trials of personalized risk-adapted BC screening. Three ongoing, large-scale, randomized controlled clinical trials (WISDOM in the US, MyPEBS in Europe, and TBST in Italy) were identified through a search of the MEDLINE and US National Library of Medicine (ClinicalTrials.gov) databases. In these trials, women either undergo standard or personalized screening. The trials vary in methods of risk stratification and screening modalities, but all aim to examine whether personalized risk-adapted screening can safely replace the current population-based approach and lead to rates of advanced-stage BC at diagnosis comparable with those of current screening regimens. The results of these trials may change current population-based screening practices.

Indexed as

Breast NeoplasmsEarly Detection of CancerEuropeFemaleHumansItalyMass Screening

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.