Evidence map›Paper›PMID 36498489›Full record

ArticleJournal of clinical medicine2022

Pre-Diagnosis Sleep Status and Survival after a Diagnosis of Ovarian Cancer: A Prospective Cohort Study.

Xiaoying Li, Chang Gao, Yifan Wei, Zhaoyan Wen, Xinyu Li, Fanghua Liu, Tingting Gong, Shi Yan, Xue Qin, Song Gao and 2 more

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. Characteristics and associated factors of insomnia in gynecological cancer patients: A cross-sectional study.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2025
    Article
  4. 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

12 authors at 1 institution in 1 country.

Xiaoying LiDepartment of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang 110004, China.
Chang GaoDepartment of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang 110004, China.
Yifan WeiDepartment of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang 110004, China.
Zhaoyan WenDepartment of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang 110004, China.
Xinyu LiDepartment of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang 110004, China.
Fanghua LiuDepartment of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang 110004, China.
Tingting GongDepartment of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang 110004, China.
Shi YanDepartment of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang 110004, China.
Xue QinDepartment of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang 110004, China.
Song GaoDepartment of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang 110004, China.
Yuhong ZhaoDepartment of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang 110004, China.
Qijun WuDepartment of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang 110004, China.ORCID 0000-0002-6350-106X
China Medical University · CN

Funding

345 Talent Project of Shengjing Hospital of China Medical University No. M0268 and No. M0701JieBangGuaShuai Project of Liaoning Province No. 2021JH1/1040050LiaoNing Revitalization Talents Program No. XLYC1907102National Key R&D Program of China No. 2017YFC0907403Natural Science Foundation of China No. 82073647, No. 81602918, and No.82103914Shenyang high level innovative talents support program No. RC190484
6 · The paper itself

Abstract

Objective: To explore if pre-diagnosis sleep status is associated with overall survival (OS) of ovarian cancer (OC). Methods: This is a prospective cohort study of 853 OC patients newly diagnosed between 2015 and 2020. Sleep status was measured by the Pittsburgh Sleep Quality Index (PSQI). Vital status of patients was obtained through active follow-up and linkage to medical records and cancer registry. The Cox proportional hazards regression model was utilized to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for aforementioned associations. Results: During the follow-up period (median: 37.57 months, interquartile: 25.00 to 50.17 months), 123 (18.39%) OC patients died. The HR (95%CI) for OS of OC was 2.13 (1.42−3.18) for sleeping after 22:00, compared with sleeping before 22:00; 2.43 (1.64−3.62) for poor sleep quality, compared to good sleep quality; 2.26 (1.37−3.72) for late bed-early rise and 1.93 (1.09−3.42) for late bed-late rise, compared with early bed-early rise; 0.40 (0.24−0.67) for night sleep duration of ≥7.5 h/day, compared with 7−7.5 h/day; 0.53 (0.29−0.98) for total sleep duration of ≥8 h/day, compared with 7.5−8 h/day. Further, the interaction effects were significant between residual lesions and wake-up time, night bedtime, sleep pattern, and between total sleep duration and menopausal status, parity. Additionally, there was a significant curvilinear association between PSQI score and OS (p nonlinear <0.05). Conclusions: Pre-diagnosis longer total and night sleep duration were associated with better OS, whereas later sleeping time, poor sleep quality, and bad sleep patterns were associated with poor OS among OC survivors.

Indexed as

cohortovarian cancersleepsurvival

Identifiers

PMID36498489
PMCPMC9741188
OpenAlexW4310024815

What OpenQuestion 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 OpenQuestion graph.