Evidence map›Paper›PMID 28463959›Full record

Observational studyBritish journal of cancer2017

Pre-diagnosis diet and survival after a diagnosis of ovarian cancer.

Mary C Playdon, Christina M Nagle, Torukiri I Ibiebele, Leah M Ferrucci, Melinda M Protani, Jonathan Carter, Simon E Hyde, Deborah Neesham, James L Nicklin, Susan T Mayne and 1 more

Abstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in British journal of cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 4 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

37 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  18. Association between diet quality and ovarian cancer risk and survival.Journal of the National Cancer Institute · 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

11 authors.

Mary C PlaydonYale School of Public Health, Department of Chronic Disease Epidemiology, Yale University, 60 College Street, New Haven, CT 06520, USA.
Christina M NagleGynaecological Cancers Group, QIMR Berghofer Institute of Medical Research, 300 Herston Road, Herston, Queensland 4006, Australia.
Torukiri I IbiebeleGynaecological Cancers Group, QIMR Berghofer Institute of Medical Research, 300 Herston Road, Herston, Queensland 4006, Australia.
Leah M FerrucciYale School of Public Health, Department of Chronic Disease Epidemiology, Yale University, 60 College Street, New Haven, CT 06520, USA.
Melinda M ProtaniGynaecological Cancers Group, QIMR Berghofer Institute of Medical Research, 300 Herston Road, Herston, Queensland 4006, Australia.
Jonathan CarterDepartment of Gynaecological Oncology, The University of Sydney, Sydney, New South Wales 2006, Australia.
Simon E HydeMercy Hospital for Women, Department of Gynaecological Oncology, Studley Road, Heidelberg, Victoria 3084, Australia.
Deborah NeeshamOncology/Dysplasia Unit, The Royal Women's Hospital, Flemington Road, Parkville, Victoria 3052, Australia.
James L NicklinQueensland Centre for Gynaecological Cancer, Royal Brisbane and Women's Hospital, Butterfield Street, Herston, Queensland 4029, Australia.
Susan T MayneYale School of Public Health, Department of Chronic Disease Epidemiology, Yale University, 60 College Street, New Haven, CT 06520, USA.
Penelope M WebbGynaecological Cancers Group, QIMR Berghofer Institute of Medical Research, 300 Herston Road, Herston, Queensland 4006, Australia.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Yale/NCI Cooperative Training Program in Cancer EpidemiologyT32CA105666 · NCI · YALE UNIVERSITY · PI MA, XIAOMEI · 2008 to 2012
$603k
NCATS NIH HHS UL1 TR001863NCI NIH HHS T32 CA105666
6 · The paper itself

Abstract

backgroundThe relationship between diet and survival after ovarian cancer diagnosis is unclear as a result of a limited number of studies and inconsistent findings.

methodsWe examined the association between pre-diagnostic diet and overall survival in a population-based cohort (n=811) of Australian women diagnosed with invasive epithelial ovarian cancer between 2002 and 2005. Diet was measured by validated food frequency questionnaire. Deaths were ascertained up to 31 August 2014 via medical record review and Australian National Death Index linkage. We conducted Cox proportional hazards regression analysis, controlling for diagnosis age, tumour stage, grade and subtype, residual disease, smoking status, body mass index, physical activity, marital status, and energy intake.

resultsWe observed improved survival with highest compared with lowest quartile of fibre intake (hazard ratio (HR)=0.69, 95% CI: 0.53-0.90, P-trend=0.002). There was a suggestion of better survival for women with highest compared with lowest intake category of green leafy vegetables (HR=0.79, 95% CI: 0.62-0.99), fish (HR=0.74, 95% CI: 0.57-0.95), poly- to mono-unsaturated fat ratio (HR=0.76, 95% CI: 0.59-0.98), and worse survival with higher glycaemic index (HR=1.28, 95% CI: 1.01-1.65, P-trend=0.03).

conclusionsThe associations we observed between healthy components of diet pre-diagnosis and ovarian cancer survival raise the possibility that dietary choices after diagnosis may improve survival.

Indexed as

DietAgedAustraliaCohort StudiesDietary Fats, UnsaturatedDietary FiberFatty Acids, MonounsaturatedFemaleGlycemic IndexHumansMiddle AgedNeoplasm InvasivenessNeoplasms, Glandular and EpithelialOvarian NeoplasmsProportional Hazards ModelsSeafoodDietary Fats, UnsaturatedDietary FiberFatty Acids, Monounsaturated

Identifiers

PMID28463959
PMCPMC5518850

What OpenQuestion holds

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LicenceCC BY-NC-SA
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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.