Cardiovascular RiskprofilE - IMaging and gender-specific disOrders (CREw-IMAGO): rationale and design of a multicenter cohort study.

BACKGROUND: Reproductive disorders, such as polycystic ovary syndrome (PCOS), primary ovarian insufficiency (POI) and hypertensive pregnancy disorders (HPD) like pre-eclampsia (PE), are associated with an increased risk of cardiovascular disease (CVD). Detection of early signs of cardiovascular disease (CVD), as well as identification of risk factors among women of reproductive age which improve cardiovascular risk prediction, is a challenge and current models might underestimate long-term health risks. The aim of this study is to assess cardiovascular disease in patients with a history of a reproductive disorder by low-dose computed tomography (CT). METHODS: Women of 45 - 55 years, who experienced a reproductive disorder (PCOS, POI, HPD), are invited to participate in this multicenter, prospective, cohort study. Women will be recruited after regular cardiovascular screening, including assessment of classical cardiovascular risk factors. CT of the coronary arteries (both coronary artery calcium scoring (CACS), and contrast-enhanced coronary CT angiography (CCTA)) and carotid siphon calcium scoring (CSC) is planned in 300 women with HPD and 300 women with PCOS or POI. In addition, arterial stiffness (non-invasive pulse wave velocity (PWV)) measurement and cell-based biomarkers (inflammatory circulating cells) will be obtained. DISCUSSION: Initial inclusion is focused on women of 45 - 55 years. However, the age range (40 - 45 years and/or ≥ 55 years) and group composition may be adjusted based on the findings of the interim analysis. Participants can potentially benefit from information obtained in this study concerning their current cardiovascular health and expected future risk of cardiovascular events. The results of this study will provide insights in the development of CVD in women with a history of reproductive disorders. Ultimately, this study may lead to improved cardiovascular prediction models and will provide an opportunity for timely adjustment of preventive strategies. Limitations of this study include the possibility of overdiagnosis and the average radiation dose of 3.5 mSv during coronary and carotid siphon CT, although the increased lifetime malignancy risk is negligible. TRIAL REGISTRATION: Netherlands Trial Register, NTR5531 . Date registered: October 21st, 2015.

Multisite external validation of a risk prediction model for the diagnosis of blood stream infections in febrile pediatric oncology patients without severe neutropenia.

BACKGROUND: Pediatric oncology patients are at an increased risk of invasive bacterial infection due to immunosuppression. The risk of such infection in the absence of severe neutropenia (absolute neutrophil count ≥ 500/µL) is not well established and a validated prediction model for blood stream infection (BSI) risk offers clinical usefulness. METHODS: A 6-site retrospective external validation was conducted using a previously published risk prediction model for BSI in febrile pediatric oncology patients without severe neutropenia: the Esbenshade/Vanderbilt (EsVan) model. A reduced model (EsVan2) excluding 2 less clinically reliable variables also was created using the initial EsVan model derivative cohort, and was validated using all 5 external validation cohorts. One data set was used only in sensitivity analyses due to missing some variables. RESULTS: From the 5 primary data sets, there were a total of 1197 febrile episodes and 76 episodes of bacteremia. The overall C statistic for predicting bacteremia was 0.695, with a calibration slope of 0.50 for the original model and a calibration slope of 1.0 when recalibration was applied to the model. The model performed better in predicting high-risk bacteremia (gram-negative or Staphylococcus aureus infection) versus BSI alone, with a C statistic of 0.801 and a calibration slope of 0.65. The EsVan2 model outperformed the EsVan model across data sets with a C statistic of 0.733 for predicting BSI and a C statistic of 0.841 for high-risk BSI. CONCLUSIONS: The results of this external validation demonstrated that the EsVan and EsVan2 models are able to predict BSI across multiple performance sites and, once validated and implemented prospectively, could assist in decision making in clinical practice. Cancer 2017;123:3781-3790. © 2017 American Cancer Society.

American Joint Committee on Cancer acceptance criteria for inclusion of risk models for individualized prognosis in the practice of precision medicine.

The American Joint Committee on Cancer (AJCC) has increasingly recognized the need for more personalized probabilistic predictions than those delivered by ordinal staging systems, particularly through the use of accurate risk models or calculators. However, judging the quality and acceptability of a risk model is complex. The AJCC Precision Medicine Core conducted a 2-day meeting to discuss characteristics necessary for a quality risk model in cancer patients. More specifically, the committee established inclusion and exclusion criteria necessary for a risk model to potentially be endorsed by the AJCC. This committee reviewed and discussed relevant literature before creating a checklist unique to this need of AJCC risk model endorsement. The committee identified 13 inclusion and 3 exclusion criteria for AJCC risk model endorsement in cancer. The emphasis centered on performance metrics, implementation clarity, and clinical relevance. The facilitation of personalized probabilistic predictions for cancer patients holds tremendous promise, and these criteria will hopefully greatly accelerate this process. Moreover, these criteria might be useful for a general audience when trying to judge the potential applicability of a published risk model in any clinical domain. CA Cancer J Clin 2016;66:370-374. © 2016 American Cancer Society.

Prediction of preterm birth in multiple pregnancies: development of a multivariable model including cervical length measurement at 16 to 21 weeks' gestation.

OBJECTIVE: To develop a multivariable prognostic model for the risk of preterm delivery in women with multiple pregnancy that includes cervical length measurement at 16 to 21 weeks' gestation and other variables. METHODS: We used data from a previous randomized trial. We assessed the association between maternal and pregnancy characteristics including cervical length measurement at 16 to 21 weeks' gestation and time to delivery using multivariable Cox regression modelling. Performance of the final model was assessed for the outcomes of preterm and very preterm delivery using calibration and discrimination measures. RESULTS: We studied 507 women, of whom 270 (53%) delivered < 37 weeks (preterm) and 66 (13%) < 32 weeks (very preterm). Women with cervical length < 30 mm delivered more often preterm (hazard ratio 1.9; 95% CI 0.7 to 4.8). Other independently contributing predictors were previous preterm delivery, monochorionicity, smoking, educational level, and triplet pregnancy. Prediction models for preterm and very preterm delivery had a c-index of 0.68 (95% CI 0.63 to 0.72) and 0.68 (95% CI 0.62 to 0.75), respectively, and showed good calibration. CONCLUSION: In women with a multiple pregnancy, the risk of preterm delivery can be assessed with a multivariable model incorporating cervical length and other predictors.

Objectif : Élaborer un modèle pronostique multivarié (comportant la mesure de la longueur cervicale à 16 - 21 semaines de gestation et d'autres variables) pour ce qui est du risque d'accouchement préterme chez les femmes connaissant une grossesse multiple. Méthodes : Nous avons utilisé les données issues d'un essai randomisé précédent. Nous avons évalué l'association entre les caractéristiques maternelles et de grossesse (dont la mesure de la longueur cervicale à 16 - 21 semaines de gestation et le délai avant l'accouchement) au moyen du modèle de régression multivariée de Cox. Le rendement du modèle final a été évalué en fonction de critères d'évaluation traitant du moment de l'accouchement (préterme et très préterme) au moyen de mesures d'étalonnage et de discrimination. Résultats : Nous avons étudié 507 femmes, dont 270 (53 %) ont accouché < 37 semaines (préterme) et 66 (13 %) < 32 semaines (très préterme). Les femmes qui présentaient une longueur cervicale < 30 mm ont plus souvent connu un accouchement préterme (densité de l'incidence, 1,9; IC à 95 %, 0,7 - 4,8). Parmi les autres facteurs prédictifs indépendants, on trouvait les antécédents d'accouchement préterme, la monochorionicité, le tabagisme, le niveau de scolarité et la présence d'une grossesse triple. Les modèles prédictifs pour ce qui est des accouchements préterme et très préterme comptaient un indice C de 0,68 (IC à 95 %, 0,63 - 0,72) et de 0,68 (IC à 95 %, 0,62 - 0,75), respectivement, et présentaient un bon étalonnage. Conclusion : Chez les femmes qui connaissent une grossesse multiple, le risque d'accouchement préterme peut être évalué au moyen d'un modèle multivarié comportant la mesure de la longueur cervicale et d'autres facteurs prédictifs. 

Long-term quality of life after surgical intensive care admission.

OBJECTIVES: To quantify the long-term (>6 years) health-related quality of life (HRQOL) of a large cohort of patients admitted to a surgical intensive care unit (ICU). In addition, we aimed to explore the influence of different surgical classifications on long-term health status and to make comparisons with general population norms. DESIGN: Prospective observational cohort study. SETTING: A Dutch teaching hospital. PATIENTS: All surviving surgical ICU patients admitted to the Dutch teaching hospital between 1995 and 2000. MAIN OUTCOME MEASURES: Patient-reported data on HRQOL were collected with the EuroQol-6D (EQ-6D) after a mean follow-up of 8 years (range, 6-11 years). Patient characteristics, surgical classification, length of ICU stay, and survival were prospectively registered. The EQ utility scores (measured with the EQ-5D US index tariff), EQ visual analog scale scores, and prevalences of domain-specific health problems were calculated. The effect of surgical classification on EQ utility scores and EQ visual analog scale scores was assessed by multivariable generalized linear regression analysis. Logistic regression was used to explore the influence of surgical classification on domain-specific health problems. Long-term HRQOL of surgical ICU patients was compared with an age- and sex-matched general Dutch population using t test analysis. RESULTS: Eight hundred thirty-four patients survived the ICU and were available for follow-up. In 575 patients (69%), the HRQOL was measured. For all surgical classifications combined, after 6 to 11 years, nearly half of all patients still had problems with mobility (52%), usual activity (52%), pain/discomfort (57%), and cognition (43%). Compared with the age- and sex-matched general population, HRQOL was worse, with a difference of 0.11 on the EQ utility score (range, 0-1). Oncological surgery patients had the best (EQ utility score, 0.83) and vascular patients had the worst (EQ utility score, 0.72) HRQOL. Trauma (odds ratio between 2.47-3.47) and vascular surgery (odds ratio between 2.27-5.37) patients showed significantly increased prevalences of problems in mobility, self-care, usual activities, and cognition. CONCLUSIONS: More than 6 years after a surgical ICU admission, HRQOL of this patient population is largely reduced. Many patients still have a variety of health problems, including decreased cognitive functioning. Treatment advances should be made to reduce the current health deficit of surgical ICU survivors compared with the general population.

Regional trauma system reduces mortality and changes admission rates: a before and after study.

OBJECTIVE: To evaluate the effect of the introduction of a regionalized trauma system. BACKGROUND: Trauma systems have proven to be efficacious in reducing mortality in trauma patients in the United States. To date, this was not proven for inclusive trauma systems outside the United States. The current study evaluates the effect of the introduction of an inclusive trauma system in the Netherlands in 1999. METHODS: Retrospective pre- and post analyses of a trauma care system on hospital discharge data regarding trauma patients admitted to hospitals in the central region of The Netherlands. Patients treated during 1996 to 1998 (control group), before implementation of the inclusive trauma system were compared with patients treated during 2003 to 2005 (index group) after the trauma system was installed. Risk adjusted odds-ratios of death and admission to a trauma center were determined. RESULTS: A total of 33,201 patients were included in the control group and compared with 34,840 patients in the index group. After implementation of the trauma system, in-hospital mortality for all injured patients decreased from 2.6% to 2.3% (OR: 0.89 with 95% CI: 0.80-0.98). After adjustment for differences in gender, age, injury severity, comorbidity, injured body region, mechanism and intent of injury between both groups, the odds-ratio was 0.84 with 95% CI (0.76-0.94). Multitrauma patients were the subgroup admitted more frequently to a trauma center (OR: 1.19 with 95% CI: 1.01-1.39). CONCLUSIONS: Implementation of an inclusive trauma system in The Netherlands results in a more efficient triage system of trauma patients among hospitals and is associated with a substantial and statistically significant risk reduction (16%) of death.