244 research outputs found
Levels of State and Trait Anxiety in Patients Referred to Ophthalmology by Primary Care Clinicians: A Cross Sectional Study
Purpose There is a high level of over-referral from primary eye care leading to significant numbers of people without ocular pathology (false positives) being referred to secondary eye care. The present study used a psychometric instrument to determine whether there is a psychological burden on patients due to referral to secondary eye care, and used Rasch analysis to convert the data from an ordinal to an interval scale. Design Cross sectional study. Participants and Controls 322 participants and 80 control participants. Methods State (i.e. current) and trait (i.e. propensity to) anxiety were measured in a group of patients referred to a hospital eye department in the UK and in a control group who have had a sight test but were not referred. Response category analysis plus infit and outfit Rasch statistics and person separation indices were used to determine the usefulness of individual items and the response categories. Principal components analysis was used to determine dimensionality. Main Outcome Measure Levels of state and trait anxiety measured using the State-Trait Anxiety Inventory. Results State anxiety scores were significantly higher in the patients referred to secondary eye care than the controls (p0.1). Rasch analysis highlighted that the questionnaire results needed to be split into “anxiety-absent” and “anxiety-present” items for both state and trait anxiety, but both subscales showed the same profile of results between patients and controls. Conclusions State anxiety was shown to be higher in patients referred to secondary eye care than the controls, and at similar levels to people with moderate to high perceived susceptibility to breast cancer. This suggests that referral from primary to secondary eye care can result in a significant psychological burden on some patients
An epidemiological model for prediction of endometrial cancer risk in Europe
Endometrial cancer (EC) is the fourth most frequent cancer in women in Europe, and as its incidence is increasing, prevention strategies gain further pertinence. Risk prediction models can be a useful tool for identifying women likely to benefit from targeted prevention measures. On the basis of data from 201,811 women (mostly aged 30–65 years) including 855 incident EC cases from eight countries in the European Prospective Investigation into Cancer and Nutrition cohort, a model to predict EC was developed. A step-wise model selection process was used to select confirmed predictive epidemiologic risk factors. Piece-wise constant hazard rates in 5-year age-intervals were estimated in a cause-specific competing risks model, five-fold-cross-validation was applied for internal validation. Risk factors included in the risk prediction model were body-mass index (BMI), menopausal status, age at menarche and at menopause, oral contraceptive use, overall and by different BMI categories and overall duration of use, parity, age at first full-term pregnancy, duration of menopausal hormone therapy and smoking status (specific for pre, peri- and post-menopausal women). These variables improved the discriminating capacity to predict risk over 5 years from 71 % for a model based on age alone to 77 % (overall C statistic), and the model was well-calibrated (ratio of expected to observed cases = 0.99). Our model could be used for the identification of women at increased risk of EC in Western Europe. To achieve an EC-risk model with general validity, a large-scale cohort-consortium approach would be needed to assess and adjust for population variation
Different measures of smoking exposure and mammographic density in postmenopausal Norwegian women: a cross-sectional study
Background: Recent cohort studies have suggested an
increased risk of breast cancer with long duration of smoking,
and with smoking initiation before first birth. Cigarette smoking
may have both carcinogenic effects and antiestrogenic effects
on the breast tissue. We decided to examine the relationship
between different measures of smoking exposure and
mammographic density.
Methods: Lifetime smoking history was collected through
interview and questionnaires among 907 postmenopausal
participants in the Tromsø Mammography and Breast Cancer
study. The mammograms were obtained from the governmental
Norwegian Breast Cancer Screening Program. Mammograms
were classified according to the percentage and absolute
mammographic densities using a previously validated computerassisted
method.
Results:Sixty-five percent of the women reported having ever
smoked cigarettes, while 34% were current smokers. After
adjustment for age, age at first birth, parity, age at menopause,
postmenopausal hormone therapy use, and body mass index,
smoking was inversely associated with both measures of
mammographic density (both trends P < 0.01). Both current
smokers and former smokers had significantly lower adjusted
mean percentage mammographic density compared with never
smokers (P = 0.003 and P = 0.006, respectively). An inverse
dose–response relationship with mammographic density was
found between both the number of cigarettes and the number of
pack-years smoked among current smokers. Current smokers
who smoked 11 cigarettes or more daily had a 3.7% absolute
(36% relative difference) lower percentage mammographic
density compared with current smokers who smoked seven
cigarettes or less daily (P = 0.008). When former smokers were
stratified according to time since smoking cessation, we found
that women who had stopped smoking less than 24 years ago
had a significantly lower mean percentage mammographic
density compared with never smokers (P < 0.001).
Conclusion: We found modest inverse dose–response
associations between numbers of cigarettes and of pack-years
smoked and both measures of mammographic density among
current smokers. Former smokers who had stopped smoking
less than 24 years ago also had a statistically significantly lower
mean percentage mammographic density when compared with
never smokers. These findings are consistent with an
antiestrogenic effect of cigarette smoking on the breast tissue
Simulation modeling for stratified breast cancer screening : a systematic review of cost and quality of life assumptions
BACKGROUND: The economic evaluation of stratified breast cancer screening gains momentum, but produces also very diverse results. Systematic reviews so far focused on modeling techniques and epidemiologic assumptions. However, cost and utility parameters received only little attention. This systematic review assesses simulation models for stratified breast cancer screening based on their cost and utility parameters in each phase of breast cancer screening and care. METHODS: A literature review was conducted to compare economic evaluations with simulation models of personalized breast cancer screening. Study quality was assessed using reporting guidelines. Cost and utility inputs were extracted, standardized and structured using a care delivery framework. Studies were then clustered according to their study aim and parameters were compared within the clusters. RESULTS: Eighteen studies were identified within three study clusters. Reporting quality was very diverse in all three clusters. Only two studies in cluster 1, four studies in cluster 2 and one study in cluster 3 scored high in the quality appraisal. In addition to the quality appraisal, this review assessed if the simulation models were consistent in integrating all relevant phases of care, if utility parameters were consistent and methodological sound and if cost were compatible and consistent in the actual parameters used for screening, diagnostic work up and treatment. Of 18 studies, only three studies did not show signs of potential bias. CONCLUSION: This systematic review shows that a closer look into the cost and utility parameter can help to identify potential bias. Future simulation models should focus on integrating all relevant phases of care, using methodologically sound utility parameters and avoiding inconsistent cost parameters
Reproductive and hormone-related risk factors for epithelial ovarian cancer by histologic pathways, invasiveness and histologic subtypes: results from the EPIC cohort
Whether risk factors for epithelial ovarian cancer (EOC) differ by subtype (i.e., dualistic pathway of carcinogenesis, histologic subtype) is not well understood; however, data to date suggest risk factor differences. We examined associations between reproductive and hormone-related risk factors for EOC by subtype in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Among 334,126 women with data on reproductive and hormone-related risk factors (follow-up: 1992–2010), 1,245 incident cases of EOC with known histology and invasiveness were identified. Data on tumor histology, grade, and invasiveness, were available from cancer registries and pathology record review. We observed significant heterogeneity by the dualistic model (i.e., type I [low grade serous or endometrioid, mucinous, clear cell, malignant Brenner] vs. type II [high grade serous or endometrioid]) for full-term pregnancy (phet = 0.02). Full-term pregnancy was more strongly inversely associated with type I than type II tumors (ever vs. never: type I: relative risk (RR) 0.47 [95% confidence interval (CI): 0.33–0.69]; type II, RR: 0.81 [0.61–1.06]). We observed no significant differences in risk in analyses by major histologic subtypes of invasive EOC (serous, mucinous, endometrioid, clear cell). None of the investigated factors were associated with borderline tumors. Established protective factors, including duration of oral contraceptive use and full term pregnancy, were consistently inversely associated with risk across histologic subtypes (e.g., ever full-term pregnancy: serous, RR: 0.73 [0.58–0.92]; mucinous, RR: 0.53 [0.30–0.95]; endometrioid, RR: 0.65 [0.40–1.06]; clear cell, RR: 0.34 [0.18–0.64]; phet = 0.16). These results suggest limited heterogeneity between reproductive and hormone-related risk factors and EOC subtypes
The Influence of hormonal factors on the risk of developing cervical cancer and pre-cancer: results from the EPIC cohort
Percentage density, Wolfe's and Tabár's mammographic patterns: agreement and association with risk factors for breast cancer
INTRODUCTION: The purpose of this report was to classify mammograms according to four methods and to examine their agreement and their relationship to selected risk factors for breast cancer. METHOD: Mammograms and epidemiological data were collected from 987 women, aged 55 to 71 years, attending the Norwegian Breast Cancer Screening Program. Two readers each classified the mammograms according to a quantitative method (Cumulus or Madena software) and one reader according to two qualitative methods (Wolfe and Tabár patterns). Mammograms classified in the reader-specific upper quartile of percentage density, Wolfe's P2 and DY patterns, or Tabár's IV and V patterns, were categorized as high-risk density patterns and the remaining mammograms as low-risk density patterns. We calculated intra-reader and inter-reader agreement and estimated prevalence odds ratios of having high-risk mammographic density patterns according to selected risk factors for breast cancer. RESULTS: The Pearson correlation coefficient was 0.86 for the two quantitative density measurements. There was moderate agreement between the Wolfe and Tabár classifications (Kappa = 0.51; 95% confidence interval 0.46 to 0.56). Age at screening, number of children and body mass index (BMI) showed a statistically significant inverse relationship with high-risk density patterns for all four methods (all P < 0.05). After adjustment for percentage density, the Wolfe classification was not associated with any of the risk factors for breast cancer, whereas the association with number of children and BMI remained statistically significant for the Tabár classification. Adjustment for Wolfe or Tabár patterns did not alter the associations between these risk factors and percentage mammographic density. CONCLUSION: The four assessments methods seem to capture the same overall associations with risk factors for breast cancer. Our results indicate that the quantitative methods convey additional information over the qualitative methods
Interaction of dense breast patterns with other breast cancer risk factors in a case–control study
Smoking duration before first childbirth: an emerging risk factor for breast cancer? Results from 302,865 Norwegian women
This article is part of Eivind Bjerkaas' doctoral thesis which is available in Munin at http://hdl.handle.net/10037/6799Purpose: Recently, The International Agency for Research on Cancer classified cigarette smoking as possibly carcinogenic to the human breast. Since some new cohort studies have suggested that this risk is confined to women who started to smoke before first childbirth, we wanted to examine the association between smoking and breast cancer, with a focus on time of smoking initiation in relation to the first childbirth.
Methods: We followed 302,865 Norwegian women born between 1899 and 1975, recruited from 1974 to 2003, by linkage to national registries through December 2007. We used Cox proportional hazard models to estimate hazard ratios (HR) and 95 % confidence intervals (CI).
Results: During more than 4.1 million person-years of follow-up, we ascertained 7,490 cases of primary invasive breast cancer. Compared with never smokers, ever smokers had a 15 % (HR = 1.15, 95 % CI 1.10–1.21) increased risk of breast cancer overall and also a significantly increased risk of breast cancer in the three most exposed categories of age at smoking initiation (parous women), number of cigarettes smoked per day, years of smoking duration and number of pack-years. Ever smokers who started to smoke more than 1 year after the first childbirth had not an increased risk (HR = 0.93, 95 % CI 0.86–1.02), while those who initiated smoking more than 10 years before their first childbirth had a 60 % (HR = 1.60, 95 % CI 1.42–1.80) increased risk of breast cancer, compared with never smokers
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