Evidence map›Paper›PMID 31721037›Full record

ArticleJournal of cancer survivorship : research and practice2020

Predictors of post-cancer diagnosis resignation among Japanese cancer survivors.

Motoki Endo, Go Muto, Yuya Imai, Kiyomi Mitsui, Katsuji Nishimura, Kazuhiko Hayashi

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of cancer survivorship : research and practice, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.1field-weighted citation impact, top 20% 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

10 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Return to work experience on structural constraints and gendered differences among nasopharyngeal carcinoma survivors: a qualitative study.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
    Article
  3. Article
  4. Article
  5. Observational
  6. What can surgeons do to prevent job leave soon after cancer diagnosis? A brief report on colorectal cancer survivors in Japan.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2023
    Article
  7. Article
  8. Article
  9. Article
  10. Introduction to special section on: current topics in cancer survivorship and work.Journal of cancer survivorship : research and practice · 2020
    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

6 authors at 5 institutions in 1 country.

Motoki EndoDepartment of Public Health, Juntendo University Faculty of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan. mo-endo@juntendo.ac.jp.ORCID http://orcid.org/0000-0002-1025-4202
Go MutoDepartment of Hygiene, Kitasato University School of Medicine, Tokyo, Japan.
Yuya ImaiDepartment of Public Health, Juntendo University Faculty of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan.
Kiyomi MitsuiDepartment of Hygiene, Public Health, and Preventive Medicine, Showa University, Tokyo, Japan.
Katsuji NishimuraDepartment of Psychiatry, Tokyo Women's Medical University School of Medicine, Tokyo, Japan.
Kazuhiko HayashiDepartment of Chemotherapy and Palliative Care, Tokyo Women's Medical University Hospital, Tokyo, Japan.
Juntendo University · JPKitasato University · JPShowa University · JPTokyo Women's Medical University · JPTokyo Women's Medical University Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeIn Japan, due to the increased incidence of cancer among the working population, it has become more important to support employees to achieve a balance between cancer treatment and work. This study aimed to clarify the predictors of resigning from employment after being diagnosed with cancer (post-cancer diagnosis [PCD] resignation) among Japanese employees.

methodsAs part of a Japanese national research project (Endo-Han), the investigators conducted a web-based survey of cancer survivors (CSs) in 2017. The investigators analyzed the risk factors for PCD resignation using a logistic regression model, including age at diagnosis, sex, cancer type, cancer stage, year of diagnosis, whether the patient held a managerial role, type of employment, and company size.

resultsOf 750 employed Japanese CSs, 93 (12.4%) resigned from their jobs. The non-managers resigned more often (14.6%) than the managers (7.6%) (p = 0.007). The temporary workers exhibited the highest PCD resignation rates (22.2%), while the PCD resignation rates of the self-employed workers and permanent workers were 15.2% and 7.6%, respectively (p < 0.001). As the result of multivariate analysis, being female (odds ratio [OR], 3.67; 95%CI, 1.71-7.87), having hematological cancer (OR, 4.23; 95%CI, 1.37-13.04), having advanced cancer (OR, 2.48; 95%CI, 1.52-4.03), and being a temporary worker (OR, 2.51; 95%CI, 1.40-4.50) were identified as predictors of PCD resignation.

conclusionsIn total, 12.4% of Japanese employees quit their jobs after being diagnosed with cancer. Being female or a temporary worker and having advanced cancer were identified as predictors of PCD resignation. Regarding cancer type, hematological cancer was most strongly associated with PCD resignation. IMPLICATION OF CANCER SURVIVORS: CSs who are females and temporary workers and have advanced cancer should be followed-up more carefully after cancer diagnosis for their work sustainability, by medical professionals, companies, and society.

Indexed as

AdultCancer SurvivorsFemaleHumansJapanMaleMiddle AgedNeoplasmsWorkYoung AdultCancer siteCancer survivors (CSs)EmploymentJapanese employeesPost-cancer diagnosis (PCD) resignation

Identifiers

PMID31721037
OpenAlexW2986888931

What OpenQuestion holds

Textmetadata
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.