Dataset Information

A conditional model predicting the 10-year annual extra mortality risk compared to the general population: a large population-based study in Dutch breast cancer patients.

ABSTRACT: OBJECTIVE:Many cancer survivors are facing difficulties in getting a life insurance; raised premiums and declinatures are common. We generated a prediction model estimating the conditional extra mortality risk of breast cancer patients in the Netherlands. This model can be used by life insurers to accurately estimate the additional risk of an individual patient, conditional on the years survived. METHODOLOGY:All women diagnosed with stage I-III breast cancer in 2005-2006, treated with surgery, were selected from the Netherlands Cancer Registry. For all stages separately, multivariable logistic regression was used to estimate annual mortality risks, conditional on the years survived, until 10 years after diagnosis, resulting in 30 models. The conditional extra mortality risk was calculated by subtracting mortality rates of the general Dutch population from the patient mortality rates, matched by age, gender and year. The final model was internally and externally validated, and tested by life insurers. RESULTS:We included 23,234 patients: 10,101 stage I, 9,868 stage II and 3,265 stage III. The final models included age, tumor stage, nodal stage, lateralization, location within the breast, grade, multifocality, hormonal receptor status, HER2 status, type of surgery, axillary lymph node dissection, radiotherapy, (neo)adjuvant systemic therapy and targeted therapy. All models showed good calibration and discrimination. Testing of the model by life insurers showed that insurability using the newly-developed model increased with 13%, ranging from 0%-24% among subgroups. CONCLUSION:The final model provides accurate conditional extra mortality risks of breast cancer patients, which can be used by life insurers to make more reliable calculations. The model is expected to increase breast cancer patients' insurability and transparency among life insurers.

SUBMITTER: van Maaren MC

PROVIDER: S-EPMC6345454 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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A conditional model predicting the 10-year annual extra mortality risk compared to the general population: a large population-based study in Dutch breast cancer patients.

van Maaren Marissa C MC Kneepkens Robert F RF Verbaan Joke J Huijgens Peter C PC Lemmens Valery E P P VEPP Verhoeven Rob H A RHA Siesling Sabine S

PloS one 20190124 1

<h4>Objective</h4>Many cancer survivors are facing difficulties in getting a life insurance; raised premiums and declinatures are common. We generated a prediction model estimating the conditional extra mortality risk of breast cancer patients in the Netherlands. This model can be used by life insurers to accurately estimate the additional risk of an individual patient, conditional on the years survived.<h4>Methodology</h4>All women diagnosed with stage I-III breast cancer in 2005-2006, treated ...[more]

PMID: 30677053

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Project description:BACKGROUND:General Practitioners (GPs) play a key role in the healthcare trajectory of patients. If the patient experiences problems that are typically non-life-threatening, such as the symptoms of post-intensive-care syndrome, the GP will be the first healthcare professional they consult. The primary aim of this study is to gain insight in the frequency of GP consultations during the year before hospital admission and the year after discharge for ICU survivors and a matched control group from the general population. The secondary aim of this study is to gain insight into differences between subgroups of the ICU population with respect to the frequency of GP consultations. METHODS:We conducted a retrospective cohort study, combining a national health insurance claims database and a national quality registry for ICUs. Clinical data of patients admitted to an ICU in 2013 were enriched with claims data from the years 2012, 2013 and 2014. Poisson regression was used to assess the differences in frequency of GP consultations between the ICU population and the control group. RESULTS:ICU patients have more consultations with GPs during the year before and after admission than individuals in the control group. In the last four weeks before admission, ICU patients have 3.58 (CI 3.37; 3.80) times more GP consultations than the control group, and during the first four weeks after discharge they have 4.98 (CI 4.74; 5.23) times more GP consultations. In the year after hospital discharge ICU survivors have an increased GP consultation rate compared to the year before their hospital admission. CONCLUSIONS:Close to hospital admission and shortly after hospital discharge, the frequency of GP consultations substantially increases in the population of ICU survivors. Even a year after hospital discharge, ICU survivors have increased GP consultation rates. Therefore, GPs should be well informed about the problems ICU patients suffer after discharge, in order to provide suitable follow-up care.

Project description:PURPOSE:To systematically investigate the frequency and types of allegations related to radiology practice handled by the Dutch Medical Disciplinary Court in the past 10 years. METHODS:The Dutch Medical Disciplinary Court database was searched for verdicts concerning radiology practice between 2010 and 2019. The association between the number of verdicts and time (years) was assessed by Spearman's rho. Other data were summarized using descriptive statistics. RESULTS:There were 48 verdicts (mean 4.8 per year). There was no significant association between the number of verdicts and time (Spearman's rho <?0.001, p?=?0.99). Most allegations were in breast imaging and musculoskeletal radiology (each 18.8%), followed by interventional radiology, head and neck imaging, and abdominal imaging (each 12.5%), neuroradiology and vascular imaging (each 10.4%), and chest imaging (4.2%). There were 46 allegations against radiologists (95.8%) and 2 against residents (4.2%). The most common allegation (37.5%) was error in diagnosis. In 20.8% of verdicts, the allegation was judged (partially) founded; disciplinary measures were warnings (n?=?8) and reprimands (n?=?2). An appeal was submitted by the patient in 11 cases and by the radiologist in 3 cases. All appeals by patients were rejected, whereas 2 of the 3 appeals by radiologists were granted and previously imposed disciplinary measures were reversed. CONCLUSION:Allegations against radiologists at the Dutch Medical Disciplinary Court are relatively few, their number has remained stable over the past 10 years, and a minority were judged to be (partially) founded. We can learn from the cases presented in this article, which may improve patient care. KEY POINTS:• The frequency of allegations against radiologists at the Dutch Medical Disciplinary Court is relatively low and has not exhibited any temporal change over the past 10 years. • These allegations reflect patient dissatisfaction, but this infrequently equals malpractice. • Knowledge of the circumstances under which these allegations have arisen may improve patient care.

Dataset Information

A conditional model predicting the 10-year annual extra mortality risk compared to the general population: a large population-based study in Dutch breast cancer patients.

Publications

A conditional model predicting the 10-year annual extra mortality risk compared to the general population: a large population-based study in Dutch breast cancer patients.

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