南非夸祖鲁-纳塔尔省三所主要公立医院癌症病例的空间分布

IF 2.4 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Cancer Informatics Pub Date : 2021-07-05 eCollection Date: 2021-01-01 DOI:10.1177/11769351211028194
Mpho Ktn Motlana, Themba G Ginindza, Aweke A Mitku, Nkosana Jafta
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引用次数: 2

摘要

背景:癌症等非传染性疾病正在对卫生系统构成挑战,特别是在低收入和中等收入国家。在南非,由于缺乏全面的癌症监测系统,癌症报告不足。由于对癌症负担程度的认识有限,导致公共卫生资源的分配不准确。本研究的目的是描述夸祖鲁-纳塔尔省3个主要公共肿瘤机构的癌症发病率和癌症病例的空间分布。方法:采用回顾性研究方法,从2015 - 2017年的医疗记录中提取癌症病例。粗略的发病率估计了在此期间报告的所有癌症病例和不同类型的癌症。根据夸祖鲁-纳塔尔省的地区人口数据,每年按年龄组和性别计算每10万人的年龄标准化发病率(ASR)。使用ASR对11个地区的癌症诊断发病率进行比较。利用Choropleth空间图和Moran's指数评估ASR癌症的空间分布和区域间的地理格局。使用一个样本卡方检验来评估随时间的显著增加/减少。结果:由于研究不完整,丢失了大量病例。2015年至2017年期间,共有4909例新发癌症病例,其中62%为女性。uMgungundlovu和eThekwini县的男性和女性ASR在夸祖鲁-纳塔尔省各区中都是最高的(每10万名男性每年83.6人,每10万名女性每年158.2人,每10万名男性每年60.1人,每10万名女性每年96.9人)。观察到夸祖鲁-纳塔尔省报告的癌症病例随机分布,高度集中在2个大都市区及其周围。区域间年际差异显著,空间分布随机。总体而言,2015年至2017年,该省癌症发病率显著下降(P < 0.05)。结论:研究中的总体癌症发病率表明,女性癌症(乳腺癌和宫颈癌)仍在上升,仍然需要优先考虑,因为它们在夸祖鲁-纳塔尔省最为普遍。利用空间分析(choropleth maps)显示了该省西北部地区癌症发病率较高的模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Spatial Distribution of Cancer Cases Seen in Three Major Public Hospitals in KwaZulu-Natal, South Africa.

Spatial Distribution of Cancer Cases Seen in Three Major Public Hospitals in KwaZulu-Natal, South Africa.

Spatial Distribution of Cancer Cases Seen in Three Major Public Hospitals in KwaZulu-Natal, South Africa.

Spatial Distribution of Cancer Cases Seen in Three Major Public Hospitals in KwaZulu-Natal, South Africa.

Background: Noncommunicable diseases (NCDs) like cancer are posing a challenge in the health system especially in low- and middle-income countries (LMICs). In South Africa, cancer is under-reported due to the lack of a comprehensive cancer surveillance system. The limited knowledge on the extent of cancer burden has led to inaccurate allocation of public health resources. The aim of this study was to describe cancer incidence and spatial distribution of cancer cases seen at 3 main public oncology facilities in KwaZulu-Natal.

Methods: In this retrospective study, cases of cancer observed from year 2015 to 2017 were extracted from medical records. The crude incidence rate was estimated for the total cancer cases and for different type of cancer reported over that period. Age-standardised incidence rates (ASR) per 100 000 was calculated per year using age groups and sex according to the district population data of KwaZulu-Natal. The comparisons of cancer diagnosed incidences were made between 11 districts using the ASR. Choropleth spatial maps and Moran's Index were used to assess the ASR cancer spatial distribution along with geographical patterns among the districts. One sample chi-square test was used to assess the significant increase/decrease over time.

Results: The study lost numerous cases due to incompleteness. A total of 4909 new cases were diagnosed with cancer during 2015 to 2017, 62% of which were female. Both uMgungundlovu and eThekwini districts had the highest ASR among district municipalities of KwaZulu-Natal for both male and female (83.6 per 100 000 per men year for men, 158.2 per 100 000 women per year, and 60.1 per 100 000 men per year and 96.9 per 100 000 women per year, respectively). Random distribution of reported cancer cases in KwaZulu-Natal was observed with a high concentration being in and around 2 metropolitan districts. Spatial variation showed a significant difference from year to year between the districts with the random spatial distribution. Overall, there was a significant decline of cancer incidences observed from 2015 to 2017 (P < .05) in the province.

Conclusion: The overall cancer incidence in the study shows that female cancers (breast and cervical) are still on the rise and still need to be given priority as they were most prevalent in KwaZulu-Natal. Spatial analysis (choropleth maps) was used to show a pattern of higher concentration of cancer incidence in the north-western parts of the province.

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来源期刊
Cancer Informatics
Cancer Informatics Medicine-Oncology
CiteScore
3.00
自引率
5.00%
发文量
30
审稿时长
8 weeks
期刊介绍: The field of cancer research relies on advances in many other disciplines, including omics technology, mass spectrometry, radio imaging, computer science, and biostatistics. Cancer Informatics provides open access to peer-reviewed high-quality manuscripts reporting bioinformatics analysis of molecular genetics and/or clinical data pertaining to cancer, emphasizing the use of machine learning, artificial intelligence, statistical algorithms, advanced imaging techniques, data visualization, and high-throughput technologies. As the leading journal dedicated exclusively to the report of the use of computational methods in cancer research and practice, Cancer Informatics leverages methodological improvements in systems biology, genomics, proteomics, metabolomics, and molecular biochemistry into the fields of cancer detection, treatment, classification, risk-prediction, prevention, outcome, and modeling.
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