Evidence map›Paper›PMID 35767282›Full record

ArticleCancer2022

Survival outcomes following pregnancy or assisted reproductive technologies after breast cancer: A population-based study.

J Alejandro Rauh-Hain, Jose Zubizarreta, Roni Nitecki, Alexander Melamed, Shuangshuang Fu, Kirsten Jorgensen, Paula C Brady, Valerie L Baker, Mariana Chavez-MacGregor, Sharon H Giordano and 1 more

Open access · greenAbstract read
In one paragraph

Article in Cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 2 pooled it
0.8field-weighted citation impact, top 26% 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

6 citing papers in PubMed, 2 syntheses or guidelines pooled it, 9 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Article
  6. Assessing gaps in motherhood after cancer: development and psychometric testing of the Survivorship Oncofertility Barriers Scale.International journal of gynecological cancer : official journal of the International Gynecological Cancer Society · 2023
    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 at 6 institutions in 1 country.

J Alejandro Rauh-HainDepartment of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0000-0001-9985-5954
Jose ZubizarretaDepartment of Health Care Policy, Harvard Medical School, Boston, Massachusetts, USA.
Roni NiteckiDepartment of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0000-0002-6176-9441
Alexander MelamedDivision of Gynecologic Oncology, Department of Obstetrics and Gynecology, Columbia University Vagelos College of Physicians and Surgeons, New York, New York, USA.
Shuangshuang FuDivision of Cancer Prevention and Population Sciences, Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Kirsten JorgensenDepartment of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0000-0001-7146-9701
Paula C BradyDivision of Reproductive Endocrinology, Department of Obstetrics and Gynecology, Columbia University Irving Medical Center, New York, New York, USA.ORCID 0000-0002-2225-1148
Valerie L BakerDivision of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynecology, Johns Hopkins University, Baltimore, Maryland, USA.
Mariana Chavez-MacGregorDivision of Cancer Prevention and Population Sciences, Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0000-0002-7189-0763
Sharon H GiordanoDivision of Cancer Prevention and Population Sciences, Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Nancy L KeatingDepartment of Health Care Policy, Harvard Medical School, Boston, Massachusetts, USA.
The University of Texas MD Anderson Cancer Center · USBrigham and Women's Hospital · USColumbia University · USColumbia University Irving Medical Center · USHarvard University · USJohns Hopkins University · US

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Dihua Yu · 1985 to 2026
$290.8M
Clinical and Translational Science AwardUL1TR001873 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI REILLY, MUREDACH P · 2016 to 2025
$99.0M
Institutional Career Development CoreKL2TR001874 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GENKINGER, JEANINE M., SHIMBO, DAICHI · 2016 to 2025
$13.6M
Training of Academic Gynecologic OncologistsT32CA101642 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI ANIL K SOOD, Kathleen Schmeler · 2005 to 2026
$9.2M
Obstetrical and Oncological Outcomes Among Reproductive Age Women with Gynecological and Breast CancerK08CA234333 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI RAUH-HAIN, JOSE ALEJANDRO · 2018 to 2022
$1.2M
NCATS NIH HHS KL2 TR001874NCATS NIH HHS UL1 TR001873NCI NIH HHS K08 CA234333NCI NIH HHS P30 CA016672NCI NIH HHS T32 CA101642
6 · The paper itself

Abstract

backgroundThis study sought to determine the impact of pregnancy or assisted reproductive technologies (ART) on breast-cancer-specific survival among breast cancer survivors.

methodsThe authors performed a cohort study using a novel data linkage from the California Cancer Registry, the California birth cohort, and the Society for Assisted Reproductive Technology Clinic Outcome Reporting System data sets. They performed risk-set matching in women with stages I-III breast cancer diagnosed between 2000 and 2012. For each pregnant woman, comparable women who were not pregnant at that point but were otherwise similar based on observed characteristics were matched at the time of pregnancy. After matching, Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association of pregnancy with breast-cancer-specific survival. We repeated these analyses for women who received ART.

resultsAmong 30,021 women with breast cancer, 553 had a pregnancy and 189 attempted at least one cycle of ART. In Cox proportional hazards modeling, the pregnancy group had a higher 5-year disease-specific survival rate; 95.6% in the pregnancy group and 90.6% in the nonpregnant group (HR, 0.43; 95% CI, 0.24-0.77). In women with hormone receptor-positive cancer, we found similar results (HR, 0.43; 95% CI, 0.2-0.91). In the ART analysis, there was no difference in survival between groups; the 5-year disease-specific survival rate was 96.9% in the ART group and 94.1% in the non-ART group (HR, 0.44; 95% CI, 0.17-1.13).

conclusionPregnancy and ART are not associated with worse survival in women with breast cancer. LAY SUMMARY: We sought to determine the impact of pregnancy or assisted reproductive technologies (ART) among breast cancer survivors. We performed a study of 30,021 women by linking available data from California and the Society for Assisted Reproductive Technology Clinic Outcome Reporting System. For each pregnant woman, we matched at the time of pregnancy comparable women who were not pregnant at that point but were otherwise similar based on observed characteristics. We repeated these analyses for women who received ART. We found that pregnancy and ART were not associated with worse survival.

Indexed as

Breast NeoplasmsCohort StudiesFemaleHumansPregnancyProportional Hazards ModelsRegistriesReproductive Techniques, Assistedassisted reproductive technologiesbreast cancerpregnancyrisk-set matchingsurvival

Identifiers

PMID35767282
PMCPMC9378486
OpenAlexW4283732644

What OpenQuestion holds

Textmetadata
LicenceTDM
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.