Literature DB >> 26577302

Assisted reproductive technology use and outcomes among women with a history of cancer.

Barbara Luke1, Morton B Brown2, Stacey A Missmer3, Logan G Spector4, Richard E Leach5, Melanie Williams6, Lori Koch7, Yolanda R Smith8, Judy E Stern9, G David Ball10, Maria J Schymura11.   

Abstract

STUDY QUESTION: How do the assisted reproductive technology (ART) outcomes of women presenting for ART after cancer diagnosis compare to women without cancer? SUMMARY ANSWER: The likelihood of a live birth after ART among women with prior cancer using autologous oocytes is reduced and varies by cancer diagnosis but is similar to women without cancer when donor oocytes are used. WHAT IS KNOWN ALREADY: Premenopausal patients faced with a cancer diagnosis frequently present for fertility preservation. STUDY DESIGN, SIZE, DURATION: Population-based cohort study of women treated with ART in NY, TX and IL, USA. PARTICIPANTS/MATERIALS, SETTING,
METHODS: Women with their first ART treatment between 2004 and 2009 were identified from the Society for Assisted Reproductive Technology Clinic Outcome Reporting System database and linked to their respective State Cancer Registries based on name, date of birth and social security number. Years were rounded, i.e. year 1 = 6-18 months before treatment. This study used reports of cancer from 5 years, 6 months prior to treatment until 6 months after first ART treatment. Women who only presented for embryo banking were omitted from the analysis. The likelihood of pregnancy and of live birth with ART using autologous oocytes was modeled using logistic regression, with women without prior cancer as the reference group, adjusted for woman's age, parity, cumulative FSH dosage, infertility diagnosis, number of diagnoses, number of ART cycles, State of residency and year of ART treatment. Results of the modeling are reported as adjusted odds ratios (AORs) and (95% confidence intervals). MAIN RESULTS AND THE ROLE OF CHANCE: The study population included 53 426 women; 441 women were diagnosed with cancer within 5 years prior to ART cycle start. Mean (±SD) age at cancer diagnosis was 33.4 ± 5.7 years; age at start of ART treatment was 34.9 ± 5.8 for women with cancer compared with 35.3 ± 5.3 years for women without cancer (P = 0.03). Live birth rates among women using autologous oocytes differed substantially by cancer status (47.7% without cancer versus 24.7% with cancer, P < 0.0001), and cancer diagnosis (ranging from 53.5% for melanoma to 14.3% for breast cancer, P < 0.0001. The live birth rates among women using donor oocytes did not vary significantly by cancer status (60.4% for women with any cancer versus 64.5% for women without cancer), or by cancer diagnosis (ranging from 57.9% for breast cancer to 63.6% for endocrine cancer). Women with breast cancer make up about one-third of all cancers in this cohort. Among women with breast cancer, 2.8% of the 106 women who underwent ART within 6 months of being diagnosed with cancer used donor oocytes compared with 34.8% of the 46 women who received ART treatment a longer time after being diagnosed with cancer (P < 0.0001). We conjecture that the former group were either unaware that they had cancer or decided to undergo ART therapy prior to cancer treatment. However, their live birth rate was only 11.7% compared with 28.8%, the overall live birth rate for all women with cancer using autologous oocytes (P < 0.0001). The live birth rate for women diagnosed with breast cancer more than 6 months before ART (23.3%) did not differ significantly from the overall live birth rate for cancer (P = 0.49). If this difference is substantiated by a larger study, it would indicate a negative effect of severe recent illness itself on ART success, rather than the poor outcome being only related to the destructive effects of chemotherapies on ovarian follicles. Alternatively, because of the short time difference between cancer diagnosis and ART treatment, these pre-existing cancers may have been detected due to the increased medical surveillance during ART therapy. In women who only used autologous oocytes, women with prior cancers were significantly less likely to become pregnant and to have a live birth than those without cancer (adjusted odds ratio (AOR): 0.34, [95% confidence interval (CI): 0.27, 0.42] and 0.36 [0.28, 0.46], respectively). This was also evident with specific cancer diagnoses: breast cancer (0.20 [0.13, 0.32] and 0.19 [0.11, 0.30], respectively), cervical cancer (0.36 [0.15, 0.87] and 0.33 [0.13, 0.84], respectively) and all female genital cancers (0.49 [0.27, 0.87] and 0.47 [0.25, 0.86], respectively). Of note, among women with cancer who became pregnant, their likelihood of having a live birth did not differ significantly from women without cancer (85.8 versus 86.7% for women using autologous oocytes, and 85.3 versus 86.9% for women using donor oocytes). LIMITATIONS, REASONS FOR CAUTION: Women may not have been residents of the individual States for the entire 5-year pre-ART period, and therefore some cancers may not have been identified through this linkage. As a result, the actual observed number of cancers may be an underestimate. In addition, the overall prevalence is low due to the age distributions. Also, because we restricted the pre-ART period to 5 years prior, we would not have identified women who were survivors of early childhood cancers (younger than age 13 years at cancer diagnosis), or who had ART more than 5 years after being diagnosed with cancer. Additional analyses are currently underway evaluating live birth outcomes after embryo banking among women with cancer prior to ART, cycles which were excluded from the analyses in this paper. Future studies are planned which will include more States, as well as linkages to vital records to obtain information on spontaneous conceptions and births, to further clarify some of the issues raised in this analysis. WIDER IMPLICATIONS OF THE
FINDINGS: Since the live birth rates using donor oocytes were not reduced in women with a prior cancer, but were reduced with autologous cycles, this suggests that factors acting in the pre- or peri-conceptional periods may be responsible for the decline. STUDY FUNDING/COMPETING INTERESTS: The study was funded by grant R01 CA151973 from the National Cancer Institute, National Institutes of Health, USA. B.L. is a research consultant for the Society for Assisted Reproductive Technology. All other authors report no conflict of interest.
© The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  assisted reproduction; breast cancer; cancer among women; cohort study; live births; oncofertility

Mesh:

Year:  2015        PMID: 26577302      PMCID: PMC4677965          DOI: 10.1093/humrep/dev288

Source DB:  PubMed          Journal:  Hum Reprod        ISSN: 0268-1161            Impact factor:   6.918


  16 in total

1.  Cycle 1 as predictor of assisted reproductive technology treatment outcome over multiple cycles: an analysis of linked cycles from the Society for Assisted Reproductive Technology Clinic Outcomes Reporting System online database.

Authors:  Judy E Stern; Morton B Brown; Barbara Luke; Ethan Wantman; Avi Lederman; Mark D Hornstein
Journal:  Fertil Steril       Date:  2010-07-18       Impact factor: 7.329

2.  Women with cancer undergoing ART for fertility preservation: a cohort study of their response to exogenous gonadotropins.

Authors:  Jaime M Knopman; Nicole Noyes; Sheeva Talebian; Lewis C Krey; James A Grifo; Frederick Licciardi
Journal:  Fertil Steril       Date:  2008-09-18       Impact factor: 7.329

Review 3.  Outcome of patients with pregnancy during or after breast cancer: a review of the recent literature.

Authors:  J Raphael; M E Trudeau; K Chan
Journal:  Curr Oncol       Date:  2015-03       Impact factor: 3.677

4.  Cumulative birth rates with linked assisted reproductive technology cycles.

Authors:  Barbara Luke; Morton B Brown; Ethan Wantman; Avi Lederman; William Gibbons; Glenn L Schattman; Rogerio A Lobo; Richard E Leach; Judy E Stern
Journal:  N Engl J Med       Date:  2012-06-28       Impact factor: 91.245

5.  Prognostic impact of pregnancy after breast cancer according to estrogen receptor status: a multicenter retrospective study.

Authors:  Hatem A Azim; Niels Kroman; Marianne Paesmans; Shari Gelber; Nicole Rotmensz; Lieveke Ameye; Leticia De Mattos-Arruda; Barbara Pistilli; Alvaro Pinto; Maj-Britt Jensen; Octavi Cordoba; Evandro de Azambuja; Aron Goldhirsch; Martine J Piccart; Fedro A Peccatori
Journal:  J Clin Oncol       Date:  2012-11-19       Impact factor: 44.544

6.  Calculating cumulative live-birth rates from linked cycles of assisted reproductive technology (ART): data from the Massachusetts SART CORS.

Authors:  Judy E Stern; Morton B Brown; Barbara Luke; Ethan Wantman; Avi Lederman; Stacey A Missmer; Mark D Hornstein
Journal:  Fertil Steril       Date:  2009-07-10       Impact factor: 7.329

7.  Female cancer survivors are low responders and have reduced success compared with other patients undergoing assisted reproductive technologies.

Authors:  Sara E Barton; Stacey A Missmer; Katharine F Berry; Elizabeth S Ginsburg
Journal:  Fertil Steril       Date:  2011-12-15       Impact factor: 7.329

8.  Cancer survivors in the United States: prevalence across the survivorship trajectory and implications for care.

Authors:  Janet S de Moor; Angela B Mariotto; Carla Parry; Catherine M Alfano; Lynne Padgett; Erin E Kent; Laura Forsythe; Steve Scoppa; Mark Hachey; Julia H Rowland
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2013-03-27       Impact factor: 4.254

Review 9.  Infertility in reproductive-age female cancer survivors.

Authors:  Jennifer M Levine; Joanne Frankel Kelvin; Gwendolyn P Quinn; Clarisa R Gracia
Journal:  Cancer       Date:  2015-02-03       Impact factor: 6.860

10.  Second try: who returns for additional assisted reproductive technology treatment and the effect of a prior assisted reproductive technology birth.

Authors:  Barbara Luke; Morton B Brown; Ethan Wantman; Valerie L Baker; Daniel R Grow; Judy E Stern
Journal:  Fertil Steril       Date:  2013-08-26       Impact factor: 7.329

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2.  History of cancer and fertility treatment outcomes: a registry linkage study in Massachusetts.

Authors:  Leslie V Farland; Judy E Stern; Sunah S Hwang; Chia-Ling Liu; Howard Cabral; Richard Knowlton; Susan T Gershman; Charles C Coddington; Stacey A Missmer
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3.  Survival outcomes following pregnancy or assisted reproductive technologies after breast cancer: A population-based study.

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Journal:  Cancer       Date:  2022-06-29       Impact factor: 6.921

4.  Fertility preservation strategies for cancerous women: An updated review.

Authors:  Fatemeh Anbari; Mohammad Ali Khalili; Maryam Mahaldashtian; Alireza Ahmadi; Maria Grazia Palmerini
Journal:  Turk J Obstet Gynecol       Date:  2022-06-27

5.  The Impact of Malignancy on Assisted Reproductive Outcomes for Cancer Survivors: A Retrospective Case-Control Study.

Authors:  Yuehong Li; Xuefen Cai; Binhua Dong; Qi Wang; Xiaohui Yang; Aili Yu; Huijuan Wei; Zhanghong Ke; Pengming Sun; Beihong Zheng; Yan Sun
Journal:  Front Oncol       Date:  2022-09-16       Impact factor: 5.738

6.  "Looking at future cancer survivors, give them a roadmap": addressing fertility and family-building topics in post-treatment cancer survivorship care.

Authors:  Catherine Benedict; Jen-Ling Nieh; Alexandria L Hahn; Alyssa McCready; Michael Diefenbach; Jennifer S Ford
Journal:  Support Care Cancer       Date:  2020-09-05       Impact factor: 3.359

7.  Motherhood after breast cancer: can we balance fertility preservation and cancer treatment? A narrative review of the literature.

Authors:  Márcia M Carneiro; Ana M Cota; Maria C Amaral; Moisa L Pedrosa; Bruna O Martins; Marcelo H Furtado; Rivia M Lamaita; Marcia C F Ferreira
Journal:  JBRA Assist Reprod       Date:  2018-09-01
  7 in total

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