Recent Changes in Breast Cancer Incidence in Spain, 1980–2004

BACKGROUND: Since the 1980s, Spain experienced two decades of sharply increasing breast cancer incidence. Declines in breast cancer incidence have recently been reported in many developed countries. We examined whether a similar downturn might have taken place in Spain in recent years. METHODS: Cases of invasive female breast cancer were drawn from all population-based Spanish cancer registries that had at least 10 years of uninterrupted registration over the period 1980-2004. Overall and age-specific changes in incidence rates were evaluated using change-point Poisson models, which allow for accurate detection and estimation of trend changes. All statistical tests were two-sided. RESULTS: A total of 80,453 incident cases of invasive breast cancer were identified. Overall age- and registry-adjusted incidence rates rose by 2.9% (95% confidence interval [CI] = 2.7% to 3.1%) annually during the 1980s and 1990s; there was a statistically significant change in this trend in 2001 (95% CI = 1998 to 2004; P value for the existence of a change point <.001), after which incidence declined annually by 3.0% (95% CI = 1.8% to 4.1%). This trend differed by age group: There was a steady increase in incidence for women younger than 45 years, an abrupt downturn in 2001 for women aged 45-64 years, and a gradual leveling off in 1995 for women aged 65 years or older. Separate analyses for registries that had at least 15 years of uninterrupted registration detected a statistically significant interruption of the previous upward trend in breast cancer incidence in provinces that had aggressive breast cancer screening programs and high screening participation rates, including Navarra (change point = 1991, P < .001), Granada (change point = 2002, P = .003), Bizkaia (change point = 1998, P < .001), Gipuzkoa (change point = 1998, P = .001), and Araba (change point = 1997, P = .002). CONCLUSIONS: The recent downturn in breast cancer incidence among Spanish women older than 45 years is best explained by a period effect linked to screening saturation.Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP) (AC07-005 to M.P., PM07-004 to R.P-B.) and Carlos III Institute of Health (ISCIII-CIBERESP collaborative agreement “Acción Transversal del Cancer”).S

Is hospital discharge administrative data an appropriate source of information for cancer registries purposes? Some insights from four Spanish registries

<p>Abstract</p> <p>Background</p> <p>The use of hospital discharge administrative data (HDAD) has been recommended for automating, improving, even substituting, population-based cancer registries. The frequency of false positive and false negative cases recommends local validation.</p> <p>Methods</p> <p>The aim of this study was to detect newly diagnosed, false positive and false negative cases of cancer from hospital discharge claims, using four Spanish population-based cancer registries as the gold standard. Prostate cancer was used as a case study.</p> <p>Results</p> <p>A total of 2286 incident cases of prostate cancer registered in 2000 were used for validation. In the most sensitive algorithm (that using five diagnostic codes), estimates for Sensitivity ranged from 14.5% (CI95% 10.3-19.6) to 45.7% (CI95% 41.4-50.1). In the most predictive algorithm (that using five diagnostic and five surgical codes) Positive Predictive Value estimates ranged from 55.9% (CI95% 42.4-68.8) to 74.3% (CI95% 67.0-80.6). The most frequent reason for false positive cases was the number of prevalent cases inadequately considered as newly diagnosed cancers, ranging from 61.1% to 82.3% of false positive cases. The most frequent reason for false negative cases was related to the number of cases not attended in hospital settings. In this case, figures ranged from 34.4% to 69.7% of false negative cases, in the most predictive algorithm.</p> <p>Conclusions</p> <p>HDAD might be a helpful tool for cancer registries to reach their goals. The findings suggest that, for automating cancer registries, algorithms combining diagnoses and procedures are the best option. However, for cancer surveillance purposes, in those cancers like prostate cancer in which care is not only hospital-based, combining inpatient and outpatient information will be required.</p