Estimation of cancer cases and deaths attributable to infection in China.

Cancer Causes Control

Department of Cancer Epidemiology, Cancer Institute, Chinese Academy of Medical Sciences, 17 South Panjiayuan Lane, Beijing, 100021, People's Republic of China.

Published: August 2011

Background: The burden of cancer attributable to infection in China has not been systematically quantified in detail.

Methods: Using the findings of systematic review of prevalence of infectious agents and their relative risks (RRs) of specific cancers, a standard approach was applied to estimate the population proportions of cancers attributed to specific infectious agents in China (attributable fractions, AFs). Together with information from the latest national mortality survey and cancer registries in China, the overall and detailed numbers of cancer cases and deaths caused by infection were estimated.

Results: A total of 668,763 cancer cases and 526,567 cancer deaths were attributed to infections in China in 2005, which accounted for 25.9 and 29.4% of the overall cancer cases and deaths of the local population, respectively. More infection-related cancers in men (of ~30%) were found compared to that in women (of 25.3% cases and 21.8% deaths).

Conclusions: Infectious agents contributed more than one-quarter of the overall cancer number among population in China; further persistently effective vaccination and screening interventions and other preventive efforts against relevant infections should be initiated and strengthened.

Download full-text PDF

Source
http://dx.doi.org/10.1007/s10552-011-9791-yDOI Listing

Publication Analysis

Top Keywords

cancer cases
16
cases deaths
12
infectious agents
12
attributable infection
8
infection china
8
cancer
7
china
6
cases
5
estimation cancer
4
deaths
4

Similar Publications

Background: Most patients initially diagnosed with non-muscle invasive bladder cancer (NMIBC) still have frequent recurrence after urethral bladder tumor electrodesiccation supplemented with intravesical instillation therapy, and their risk of recurrence is difficult to predict. Risk prediction models used to predict postoperative recurrence in patients with NMIBC have limitations, such as a limited number of included cases and a lack of validation. Therefore, there is an urgent need to develop new models to compensate for the shortcomings and potentially provide evidence for predicting postoperative recurrence in NMIBC patients.

View Article and Find Full Text PDF

Background: Bladder cancer (BCa) is one of the most common malignancies worldwide, and its prognostication and treatment remains challenging. The fast growth of various cancer cells requires reprogramming of its energy metabolism using aerobic glycolysis as a major energy source. However, the prognostic and therapeutic value of glycolysis-related genes in BCa remains to be determined.

View Article and Find Full Text PDF

What Is Known About This Topic?: Global human cases of zoonotic influenza A(H5N6) have increased significantly in recent years, primarily due to widespread circulation of clade 2.3.4.

View Article and Find Full Text PDF

In recent years, new anticancer drugs have been investigated and approved for the treatment of breast cancer based on improved survival outcomes. However, these new treatments have specific class-related side effects. Pulmonary toxicity has been identified as an adverse event of special interest with everolimus, and is becoming an increasingly significant clinical challenge with the recent approval of trastuzumab deruxtecan.

View Article and Find Full Text PDF

Gastric cancer (GC), one of the tumours with the highest mortality worldwide, is not a homogeneous disease, showing different features according to location, macroscopic aspect, histotype and molecular alterations. Adenocarcinoma is the most frequent epithelial GC (95%), the remaining 5% comprising rare epithelial tumours with their peculiarities, behaviour and incidence <6 cases/100,000/year. Due to the low number of cases, many aspects must be elucidated in this context.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!