Large-Scale pathology-based cancer data - a reflection of population-based cancer data View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2002-03

AUTHORS

Yasmin Bhurgri, Sheema H. Hasan, Shahid Pervez, Naila Kayani, Akbar Shah Hussainy, Suhail Muzaffar, Mohammad Khurshid

ABSTRACT

Pathology-based cancer data is a high quality reflection of the patterns of cancer in the population it represents, provided the demographic details of the patients are carefully recorded. Relative frequency data is neither a replacement for population-based data nor a suggested alternative; it simply enhances the quality of population data and in very large data sets reflects the cancer patterns observed in the representative populations. Aware of the standard shortfalls of pathology-based data, the department of pathology, The Aga Khan University Hospital (AKUH) standardized its data, representing 53.4% of the cancer data of Karachi Division (Pakistan) and also reflecting the cancer pattern of other provinces of Pakistan. This data was compared with 4 different population and institutional-based data sets. The findings substantiate the observation that despite the problems of interpretation of data from pathology laboratories, they are an invaluable source of information on cancer patterns in much of the world where incidence data are unavailable . If developing countries, unable to organize National Population- Based Registry should as an alternate develop National Pathology-based Registers a well targeted and monitored, a Cancer Control Program would be possible. A good quality, large-scale pathology data with demographic details of the patient recorded can also be extended to give coverage to the population. More... »

PAGES

62-67

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/bf03033704

DOI

http://dx.doi.org/10.1007/bf03033704

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1020918327

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/11994766


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