Ascertaining invasive breast cancer cases; the validity of administrative and self-reported data sources in Australia

Kemp, Anna; Preen, David B.; Saunders, Christobel; Holman, C. DʼArcy J.; Bulsara, Max; Rogers, Kris; Roughead, Elizabeth E.

doi:10.1186/1471-2288-13-17

Cited by 24 publications

(32 citation statements)

References 18 publications

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“…This is the most comprehensive Australian analysis of IBR utilization patterns through a population‐based study. The NSW hospitalization data have been demonstrated to have high sensitivity and specificity in identifying patients with breast cancer when validated against cancer registry data . However, we acknowledge the potential for miscoding within administrative datasets.…”

Section: Discussionmentioning

confidence: 96%

Patterns of immediate breast reconstruction in New South Wales, Australia: a population‐based study

Feng

Flitcroft

Leeuwen

et al. 2019

ANZ Journal of Surgery

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BackgroundThe rate of immediate breast reconstruction (IBR) following mastectomy for breast cancer in Australia is low and varies between regions. To date, no previous Australian studies have examined IBR rates between all hospitals within a particular jurisdiction, despite hospitals being an important known contributor to variation in IBR rates in other countries.MethodsWe used cross‐classified random‐effects logistic regression models to examine the inter‐hospital variation in IBR rates by using data on 7961 women who underwent therapeutic mastectomy procedures in New South Wales (NSW) between January 2012 and June 2015. We derived IBR rates by patient‐, residential neighbourhood‐ and hospital‐related factors and investigated the underlying drivers for the variation in IBR.ResultsWe estimated the mean IBR rate across all hospitals performing mastectomy to be 17.1% (95% Bayesian credible interval (CrI) 12.1–23.1%) and observed wide inter‐hospital variation in IBR (variance 4.337, CrI 2.634–6.889). Older women, those born in Asian countries (odds ratio (OR) 0.5, CrI 0.4–0.6), residing in neighbourhoods with lower socioeconomic status (OR 0.7, CrI 0.5–0.8 for the most disadvantaged), and who underwent surgery in public hospitals (OR 0.4, CrI 0.1–1.0) were significantly less likely to have IBR. Women residing in non‐metropolitan areas and attending non‐metropolitan hospitals were significantly less likely to undergo IBR than their metropolitan counterparts attending metropolitan hospitals.ConclusionWide inter‐hospital variation raises concerns about potential inequities in access to IBR services and unmet demand in certain areas of NSW. Explaining the underlying drivers for IBR variation is the first step in identifying policy solutions to redress the issue.

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Section: Discussionmentioning

confidence: 96%

Patterns of immediate breast reconstruction in New South Wales, Australia: a population‐based study

Feng

Flitcroft

Leeuwen

et al. 2019

ANZ Journal of Surgery

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“…As the primary treatment of CRC is surgical, the APDC is considered to provide reliable independent data on such diagnoses. Recent studies on CRC and breast cancer have shown that cancer diagnosis can be accurately identified using hospital data 15 , 16 …”

Section: Methodsmentioning

confidence: 99%

Colorectal cancer screening and subsequent incidence of colorectal cancer: results from the 45 and Up Study

Steffen

Weber

Roder

et al. 2014

Medical Journal of Australia

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Objective: To investigate the association of colorectal cancer (CRC) screening history and subsequent incidence of CRC in New South Wales, Australia. Design, setting and participants: A total of 196 464 people from NSW recruited to the 45 and Up Study, a large Australian population‐based prospective study, by completing a baseline questionnaire distributed from January 2006 to December 2008. Individuals without pre‐existing cancer were followed for a mean of 3.78 years (SD, 0.92 years) through linkage to population health datasets. Main outcome measures: Incidence of CRC; hazard ratio (HR) according to screening history, adjusted for age, sex, body mass index, income, education, remoteness, family history, aspirin use, smoking, diabetes, alcohol use, physical activity and dietary factors. Results: Overall, 1096 cases of incident CRC accrued (454 proximal colon, 240 distal colon, 349 rectal and 53 unspecified cancers). Ever having undergone CRC screening before baseline was associated with a 44% reduced risk of developing CRC during follow‐up (HR, 0.56; 95% CI, 0.49–0.63) compared with never having undergone screening. This effect was more pronounced for those reporting endoscopy (HR, 0.50; 95% CI, 0.43–0.58) than those reporting faecal occult blood testing (FOBT) (HR, 0.61; 95% CI, 0.52–0.72). Associations for all screening exposures were strongest for rectal cancer (HR, 0.35; 95% CI, 0.27–0.45) followed by distal colon cancer (HR, 0.60; 95% CI, 0.46–0.78), while relationships were weaker for cancers of the proximal colon (HR, 0.76; 95% CI, 0.62–0.92). Conclusion: CRC incidence is lower among individuals with a history of CRC screening, through either FOBT or endoscopy, compared with individuals who have never had CRC screening, lasting for at least 4 years after screening.

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“…Various epidemiological [11,26,62] and cancer research [36] studies are based on data containing demographics and diagnosis codes of patients in New South Wales (NSW), Australia. For example, the study of [36] used the data of women over 45 who are associated with certain diagnosis and procedural codes indicating invasive breast cancer. These data were obtained from the NSW Cancer Registry and from several routinely-collected administrative and self-reported health datasets in NSW, and they were analyzed to find out their predictive power in identifying invasive breast cancer cases.…”

Section: Introductionmentioning

confidence: 99%

“…However, their authors recognize the need for algorithms that anonymize both demographics and diagnosis codes, in order to prevent identity disclosure [7] and increase data availability [36]. Also, publishing RT -datasets is important to support analysis tasks, including case count studies [46,54], which require accurately counting the number of patients associated with specific demographics and diagnosis codes, predictive modeling, and query answering [61].…”

Section: Introductionmentioning

confidence: 99%

Anonymizing datasets with demographics and diagnosis codes in the presence of utility constraints

Poulis

Loukides

Skiadopoulos

et al. 2017

Journal of Biomedical Informatics

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Publishing data about patients that contain both demographics and diagnosis codes is essential to perform large-scale, low-cost medical studies. However, preserving the privacy and utility of such data is challenging, because it requires: (i) guarding against identity disclosure (re-identification) attacks based on both demographics and diagnosis codes, (ii) ensuring that the anonymized data remain useful in intended analysis tasks, and (iii) minimizing the information loss, incurred by anonymization, to preserve the utility of general analysis tasks that are difficult to determine before data publishing. Existing anonymization approaches are not suitable for being used in this setting, because they cannot satisfy all three requirements. Therefore, in this work, we propose a new approach to deal with this problem. We enforce the requirement (i) by applying (k, k m )-anonymity, a privacy principle that prevents re-identification from attackers who know the demographics of a patient and up to m of their diagnosis codes, where k and m are tunable parameters. To capture the requirement (ii), we propose the concept of utility constraint for both demographics and diagnosis codes. Utility constraints limit the amount of generalization and are specified by data owners (e.g., the healthcare institution that performs anonymization). We also capture requirement (iii), by employing well-established information loss measures for demographics and for diagnosis codes. To realize our approach, we develop an algorithm that enforces (k, k m )-anonymity on a dataset containing both demographics and diagnosis codes, in a way that satisfies the specified utility constraints and with minimal information loss, according to the measures. Our experiments with a large dataset containing more than 200, 000 electronic health records show the effectiveness and efficiency of our algorithm.

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Ascertaining invasive breast cancer cases; the validity of administrative and self-reported data sources in Australia

Cited by 24 publications

References 18 publications

Patterns of immediate breast reconstruction in New South Wales, Australia: a population‐based study

Patterns of immediate breast reconstruction in New South Wales, Australia: a population‐based study

Colorectal cancer screening and subsequent incidence of colorectal cancer: results from the 45 and Up Study

Anonymizing datasets with demographics and diagnosis codes in the presence of utility constraints

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