Evidence map›Paper›PMID 37909210›Full record

ArticleCancer medicine2023

Impact of the COVID-19 pandemic on clinical presentation, treatments, and outcomes of new breast cancer patients: A retrospective multicenter cohort study.

Etienne Guével, Sonia Priou, Guillaume Lamé, Johanna Wassermann, Romain Bey, Catherine Uzan, Gilles Chatellier, Yazid Belkacemi, Xavier Tannier, Sophie Guillerm and 10 more

Open access · goldAbstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancer medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
2.1field-weighted citation impact, top 11% of its field
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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. 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

20 authors at 6 institutions in 1 country.

Etienne GuévelAssistance Publique-Hôpitaux de Paris, Innovation and Data, IT Department, Paris, France.
Sonia PriouAssistance Publique-Hôpitaux de Paris, Innovation and Data, IT Department, Paris, France.
Guillaume LaméCentraleSupélec, Laboratoire Génie Industriel, Université Paris-Saclay, Gif-sur-Yvette, France.ORCID 0000-0001-9514-1890
Johanna WassermannAssistance Publique-Hôpitaux de Paris, Department of medical oncology, Pitié Salpétrière University Hospital, Sorbonne Université, Paris, France.
Romain BeyAssistance Publique-Hôpitaux de Paris, Innovation and Data, IT Department, Paris, France.
Catherine UzanAssistance Publique-Hôpitaux de Paris, Institut Universitaire de cancérologie, Sorbonne Université, Paris, France.ORCID 0000-0003-3972-819X
Gilles ChatellierDepartment of medical informatics, Assistance Publique Hôpitaux de Paris, Centre-Université de Paris (APHP-CUP), Université Paris CIté, Paris, France.
Yazid BelkacemiAssistance Publique-Hôpitaux de Paris, Department of Radiation Oncology and Henri Mondor Breast Center, Henri Mondor and Albert Chenevier University Hospital, Université Paris Est Créteil, Créteil, France.
Xavier TannierSorbonne University Inserm, Université Sorbonne Paris Nord, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances pour la e-Santé, LIMICS, Paris, France.
Sophie GuillermAssistance Publique-Hôpitaux de Paris, Department of radiation therapy, Saint Louis University Hospital, Université Paris Cité, Créteil, France.
Rémi FlicoteauxAssistance Publique-Hôpitaux de Paris, Department of medical information, Paris, France.
Joseph GligorovAssistance Publique-Hôpitaux de Paris, Institut Universitaire de cancérologie, Sorbonne Université, Paris, France.ORCID 0000-0002-9900-6386
Ariel CohenAssistance Publique-Hôpitaux de Paris, Innovation and Data, IT Department, Paris, France.ORCID 0000-0002-2550-9773
Marc-Antoine BenderraAssistance Publique-Hôpitaux de Paris, Institut Universitaire de cancérologie, Sorbonne Université, Paris, France.ORCID 0000-0001-9338-0345
Luis TeixeiraAssistance Publique-Hôpitaux de Paris, Department of senology, Saint Louis Teaching Hospital, Université Paris Cité, Paris, France.
Christel DanielAssistance Publique-Hôpitaux de Paris, Innovation and Data, IT Department, Paris, France.
Barbara HersantAssistance Publique - Hôpitaux de Paris, Department of plastic surgery, Henri Mondor and Albert Chenevier University Hospital, Université Paris Est Créteil, Créteil, France.
Christophe TournigandAssistance Publique - Hôpitaux de Paris, Department of medical oncology, Henri Mondor and Albert Chenevier University Hospital, Université Paris Est Créteil, Créteil, France.
Emmanuelle KempfSorbonne University Inserm, Université Sorbonne Paris Nord, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances pour la e-Santé, LIMICS, Paris, France.ORCID 0000-0002-9285-1966
Assistance Publique-Hôpitaux de Paris (AP-HP) Cancer Group, a Cancer Research Application on Big Data (CRAB) initiative
Assistance Publique – Hôpitaux de Paris · FRSorbonne Université · FRInserm · FRUniversité Paris Cité · FRUniversité Paris-Est Créteil · FRUniversité Paris-Saclay · FR

Funding

Fondation ARC pour la Recherche sur le Cancer COVID202001343
6 · The paper itself

Abstract

backgroundThe SARS CoV-2 pandemic disrupted healthcare systems. We compared the cancer stage for new breast cancers (BCs) before and during the pandemic.

methodsWe performed a retrospective multicenter cohort study on the data warehouse of Greater Paris University Hospitals (AP-HP). We identified all female patients newly referred with a BC in 2019 and 2020. We assessed the timeline of their care trajectories, initial tumor stage, and treatment received: BC resection, exclusive systemic therapy, exclusive radiation therapy, or exclusive best supportive care (BSC). We calculated patients' 1-year overall survival (OS) and compared indicators in 2019 and 2020.

resultsIn 2019 and 2020, 2055 and 1988, new BC patients underwent cancer treatment, and during the two lockdowns, the BC diagnoses varied by -18% and by +23% compared to 2019. De novo metastatic tumors (15% and 15%, p = 0.95), pTNM and ypTNM distributions of 1332 cases with upfront resection and of 296 cases with neoadjuvant therapy did not differ (p = 0.37, p = 0.3). The median times from first multidisciplinary meeting and from diagnosis to treatment of 19 days (interquartile 11-39 days) and 35 days (interquartile 22-65 days) did not differ. Access to plastic surgery (15% and 17%, p = 0.08) and to treatment categories did not vary: tumor resection (73% and 72%), exclusive systemic therapy (13% and 14%), exclusive radiation therapy (9% and 9%), exclusive BSC (5% and 5%) (p = 0.8). Among resected patients, the neoadjuvant therapy rate was lower in 2019 (16%) versus 2020 (20%) (p = 0.02). One-year OS rates were 99.3% versus 98.9% (HR = 0.96; 95% CI, 0.77-1.2), 72.6% versus 76.6% (HR = 1.28; 95% CI, 0.95-1.72), 96.6% versus 97.8% (HR = 1.09; 95% CI, 0.61-1.94), and 15.5% versus 15.1% (HR = 0.99; 95% CI, 0.72-1.37), in the treatment groups.

conclusionsDespite a decrease in the number of new BCs, there was no tumor stage shift, and OS did not vary.

Indexed as

Breast NeoplasmsCOVID-19Cohort StudiesCommunicable Disease ControlFemaleHumansPandemicsRetrospective Studiesbreast neoplasmsCOVID-19early detection of cancerhealth services researchquality of health careroutinely collected health data

Identifiers

PMID37909210
PMCPMC10709737
OpenAlexW4388112820

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.