Advances in Cancer Survival Analysis
A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Survivorship and Quality of Life".
Deadline for manuscript submissions: 31 December 2026 | Viewed by 28
Special Issue Editors
2. Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou 310000, China
Interests: population-based evaluation of cancer prevention and early screening effectiveness (using the period method to provide timely and accurate 5-year relative survival); population-based prevention and control of cancers caused by asbestos exposure (malignant mesothelioma, lung cancer, etc.); molecular genetic epidemiology of familial tumours
Special Issues, Collections and Topics in MDPI journals
Interests: cancer epidemiology; clinical epidemiology
Special Issue Information
Dear Colleagues,
In recent years, the global cancer burden has risen sharply and is expected to continue increasing. Cancer survival is an essential indicator for the assessment of cancer burden, which reflects the level of cancer prevention and prognosis in specific regions, thus warranting focused research. However, timely and accurate evaluation of long-term survival of cancer patients remains a global technical problem. In addition, with recent advances in science and technology and the emergence of new diagnostic and therapeutic methods, there is a potential impact on cancer survival.
We are pleased to invite you to contribute to a Special Issue focusing on the analysis of cancer survival and associated factors affecting cancer survival.
This Special Issue aims to report on the most up-to-date cancer survival worldwide or in a certain area. It also seeks to further explore the relationship between emerging technologies, diagnostic and treatment methods, and other influencing factors with cancer survival.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:
- Reports on cancer survival worldwide or in certain areas;
- Assessment of cancer survival using population-based cancer registration data;
- New research advances in cancer survival;
- Application of different analytical methods in cancer survival, e.g., the period approach;
- The impact of new diagnostic and therapeutic approaches on cancer survival.
We look forward to receiving your contributions.
Prof. Dr. Tianhui (Thomas) Chen
Prof. Dr. Jianguang Ji
Prof. Dr. Jun Lyu
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- cancer burden
- cancer survival
- epidemiology
- survival analysis methodology
- cancer screening
- cancer control
- cancer prognosis
- cancer data mining
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