Abstract Background Although health economic evaluations (HEEs) are increasingly common for therapeutic interventions, they appear to be rare for the use of risk prediction models (PMs). Objectives ...To evaluate the current state of HEEs of PMs by performing a comprehensive systematic review. Methods Four databases were searched for HEEs of PM-based strategies. Two reviewers independently selected eligible articles. A checklist was compiled to score items focusing on general characteristics of HEEs of PMs, model characteristics and quality of HEEs, evidence on PMs typically used in the HEEs, and the specific challenges in performing HEEs of PMs. Results After screening 791 abstracts, 171 full texts, and reference checking, 40 eligible HEEs evaluating 60 PMs were identified. In these HEEs, PM strategies were compared with current practice (n = 32; 80%), to other stratification methods for patient management (n = 19; 48%), to an extended PM (n = 9; 23%), or to alternative PMs (n = 5; 13%). The PMs guided decisions on treatment (n = 42; 70%), further testing (n = 18; 30%), or treatment prioritization (n = 4; 7%). For 36 (60%) PMs, only a single decision threshold was evaluated. Costs of risk prediction were ignored for 28 (46%) PMs. Uncertainty in outcomes was assessed using probabilistic sensitivity analyses in 22 (55%) HEEs. Conclusions Despite the huge number of PMs in the medical literature, HEE of PMs remains rare. In addition, we observed great variety in their quality and methodology, which may complicate interpretation of HEE results and implementation of PMs in practice. Guidance on HEE of PMs could encourage and standardize their application and enhance methodological quality, thereby improving adequate use of PM strategies.
The prognosis of early-onset pre-eclampsia (before 34 weeks' gestation) is variable. Accurate prediction of complications is required to plan appropriate management in high-risk women.
To develop and ...validate prediction models for outcomes in early-onset pre-eclampsia.
Prospective cohort for model development, with validation in two external data sets.
Model development: 53 obstetric units in the UK. Model transportability: PIERS (Pre-eclampsia Integrated Estimate of RiSk for mothers) and PETRA (Pre-Eclampsia TRial Amsterdam) studies.
Pregnant women with early-onset pre-eclampsia.
Nine hundred and forty-six women in the model development data set and 850 women (634 in PIERS, 216 in PETRA) in the transportability (external validation) data sets.
The predictors were identified from systematic reviews of tests to predict complications in pre-eclampsia and were prioritised by Delphi survey.
The primary outcome was the composite of adverse maternal outcomes established using Delphi surveys. The secondary outcome was the composite of fetal and neonatal complications.
We developed two prediction models: a logistic regression model (PREP-L) to assess the overall risk of any maternal outcome until postnatal discharge and a survival analysis model (PREP-S) to obtain individual risk estimates at daily intervals from diagnosis until 34 weeks. Shrinkage was used to adjust for overoptimism of predictor effects. For internal validation (of the full models in the development data) and external validation (of the reduced models in the transportability data), we computed the ability of the models to discriminate between those with and without poor outcomes (
-statistic), and the agreement between predicted and observed risk (calibration slope).
The PREP-L model included maternal age, gestational age at diagnosis, medical history, systolic blood pressure, urine protein-to-creatinine ratio, platelet count, serum urea concentration, oxygen saturation, baseline treatment with antihypertensive drugs and administration of magnesium sulphate. The PREP-S model additionally included exaggerated tendon reflexes and serum alanine aminotransaminase and creatinine concentration. Both models showed good discrimination for maternal complications, with anoptimism-adjusted
-statistic of 0.82 95% confidence interval (CI) 0.80 to 0.84 for PREP-L and 0.75 (95% CI 0.73 to 0.78) for the PREP-S model in the internal validation. External validation of the reduced PREP-L model showed good performance with a
-statistic of 0.81 (95% CI 0.77 to 0.85) in PIERS and 0.75 (95% CI 0.64 to 0.86) in PETRA cohorts for maternal complications, and calibrated well with slopes of 0.93 (95% CI 0.72 to 1.10) and 0.90 (95% CI 0.48 to 1.32), respectively. In the PIERS data set, the reduced PREP-S model had a
-statistic of 0.71 (95% CI 0.67 to 0.75) and a calibration slope of 0.67 (95% CI 0.56 to 0.79). Low gestational age at diagnosis, high urine protein-to-creatinine ratio, increased serum urea concentration, treatment with antihypertensive drugs, magnesium sulphate, abnormal uterine artery Doppler scan findings and estimated fetal weight below the 10th centile were associated with fetal complications.
The PREP-L model provided individualised risk estimates in early-onset pre-eclampsia to plan management of high- or low-risk individuals. The PREP-S model has the potential to be used as a triage tool for risk assessment. The impacts of the model use on outcomes need further evaluation.
Current Controlled Trials ISRCTN40384046.
The National Institute for Health Research Health Technology Assessment programme.
The aim of this study was to investigate the impact of perioperative screening with modified transesophageal echocardiography (A-View method). We compared, in consecutive patients who underwent ...cardiac surgery between 2006 and 2014, 30-day mortality and in-hospital stroke incidence, operated either with perioperative modified TEE screening (intervention group) or only with conventional TEE screening (control group). Of the 8,605 study patients, modified TEE was applied in 1,391 patients (16.2%). Patients in the intervention group were on average older (71 versus 68 years, p<0.001) and more often females (31.0% versus 28.0%, p<0.001) and had a higher predicted mortality (EuroSCORE I: 5.9% versus 4.0%, p<0.001). The observed 30-day mortality was 2.2% and 2.5% in both groups, respectively, with multivariable and propensity-score adjusted relative risks (RRs) of 0.70 (95% CI: 0.50–1.00, p=0.05) and 0.67 (95% CI: 0.45–0.98, p=0.04). In-hospital stroke was 2.9% and 2.1% in both groups, respectively, with adjusted RRs of 1.03 (95% CI: 0.73–1.45) and 1.01 (95% CI: 0.71–1.43). In patients undergoing cardiac surgery, use of perioperative screening for aortic atherosclerosis with modified TEE was associated with lower postoperative mortality, but not stroke, as compared to patients operated on without such screening.
The Dutch government introduced the CoronaMelder smartphone application for digital contact tracing (DCT) to complement manual contact tracing (MCT) by Public Health Services (PHS) during the ...2020-2022 SARS-CoV-2 epidemic. Modelling studies showed great potential but empirical evidence of DCT and MCT impact is scarce. We determined reasons for testing, and mean exposure-testing intervals by reason for testing, using routine data from PHS Amsterdam (1 December 2020 to 31 May 2021) and data from two SARS-CoV-2 rapid diagnostic test accuracy studies at other PHS sites in the Netherlands (14 December 2020 to 18 June 2021). Throughout the study periods, notification of DCT-identified contacts was via PHS contact-tracers, and self-testing was not yet widely available. The most commonly reported reason for testing was having symptoms. In asymptomatic individuals, it was having been warned by an index case. Only around 2% and 2-5% of all tests took place after DCT or MCT notification, respectively. About 20-36% of those who had received a DCT or MCT notification had symptoms at the time of test request. Test positivity after a DCT notification was significantly lower, and exposure-test intervals after a DCT or MCT notification were longer, than for the above-mentioned other reasons for testing. Our data suggest that the impact of DCT and MCT on the SARS-CoV-2 epidemic in the Netherlands was limited. However, DCT impact might be enlarged if app use coverage is improved, contact-tracers are eliminated from the digital notification process to minimise delays, and DCT is combined with self-testing.
In a previous study we devised a diagnostic decision rule to improve management of children with meningeal signs, suspected of having bacterial meningitis. The decision rule aimed to guide decisions ...on (1) whether a lumbar puncture is necessary in children with meningeal signs, and (2) which children need hospitalisation and empirical antibiotic treatment for bacterial meningitis. In this study we assessed the validity of this rule in an external population of four (paediatric) hospitals in The Netherlands. The decision rule included two scoring algorithms using symptoms, signs and quickly available blood and cerebrospinal fluid (CSF) laboratory tests. To evaluate the discriminative value of both algorithms, the absolute numbers of correctly diagnosed patients and the area under the receiver operator characteristic curve were estimated, and compared with the results from the original population (n = 360). In a 18 month period, we included 226 children, median age 2.2 years, who visited the emergency department with meningeal signs. Bacterial meningitis was present in 25 (11%). Using the scoring algorithms patients could be categorised in groups of increasing risk of bacterial meningitis. The discriminative values of the clinical and CSF algorithm in this new population were similar to those in the original population. In the total population of 586 children with meningeal signs, the rule selected 205 children (35%) who did not need a lumbar puncture and 366 children who did not need empirical treatment (62%). In conclusion, this diagnostic rule performed well in a new population of children with meningeal signs. This diagnostic decision rule is a valuable tool for the clinician when deciding to treat these children for bacterial meningitis and thus improving their management.
Risk prediction models need thorough validation to assess their performance. Validation of models for survival outcomes poses challenges due to the censoring of observations and the varying time ...horizon at which predictions can be made. This article describes measures to evaluate predictions and the potential improvement in decision making from survival models based on Cox proportional hazards regression.
As a motivating case study, the authors consider the prediction of the composite outcome of recurrence or death (the "event") in patients with breast cancer after surgery. They developed a simple Cox regression model with 3 predictors, as in the Nottingham Prognostic Index, in 2982 women (1275 events over 5 years of follow-up) and externally validated this model in 686 women (285 events over 5 years). Improvement in performance was assessed after the addition of progesterone receptor as a prognostic biomarker.
The model predictions can be evaluated across the full range of observed follow-up times or for the event occurring by the end of a fixed time horizon of interest. The authors first discuss recommended statistical measures that evaluate model performance in terms of discrimination, calibration, or overall performance. Further, they evaluate the potential clinical utility of the model to support clinical decision making according to a net benefit measure. They provide SAS and R code to illustrate internal and external validation.
The authors recommend the proposed set of performance measures for transparent reporting of the validity of predictions from survival models.
Abstract
Background: Therapy of newly identified MBC is largely based on estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2) status. Optimal receptor information should be ...up-to-date and preferably from the whole body, given receptor conversion over time and intra-patient tumor heterogeneity. Novel molecular imaging by means of 18F-fluoroestradiol (FES)- and 89Zr-trastuzumab-PET/CT is a non-invasive, patient friendly way to obtain such information. Comprehensive prospective data comparing novel molecular imaging, metastasis biopsy and blood biomarkers, are needed to assess clinical utility for optimal therapy guidance and response prediction.
Trial design: The IMPACT-MBC trial (NCT01957332), is a multicenter prospective cohort study, supported by the Dutch Cancer Society-Alpe d’HuZes, in which n=200 newly diagnosed MBC patients will be entered. Prior to start of treatment patients will undergo i) standard MBC work up including bone scan, diagnostic CT and 18F-fluorodeoxyglucose(FDG)-PET/CT, ii) a metastasis biopsy, for standard (immuno)pathology and DNA sequencing, iii) 18F-FES- and 89Zr-trastuzumab-PET/CT to assess whole-body metastatic ER and HER2 status, and iv) blood sampling (CTCs, ctDNA, germline DNA, 89Zr-radioactivity measurements). Treatment advice will be based on standard work up and experimental PET scans. Tumor response is assessed by a 2 week 18F-FDG-PET/CT (experimental) and an 8 week diagnostic CT (standard; primary outcome).
Eligibility criteria: All newly diagnosed non-rapidly progressive MBC patients with measurable or clinical evaluable (bone only) disease can be enrolled, regardless of primary tumor ER and HER2 status. Patients should be eligible for systemic therapy, but not require immediate start of chemotherapy. A histological biopsy of a metastatic lesion should be safely obtainable. Excluded are pregnant or lactating women and patients with a prior allergic reaction to immunoglobulins.
Specific aims: i) To assess the (added) clinical utility of 18F-FES- and 89Zr-trastuzumab-PET/CT, in the setting of MBC at first presentation, in relation to other diagnostics, ii) to assess the relation of experimental 18F-FES-, 89Zr-trastuzumab- and 2 week 18F-FDG-PET/CT with (progression free) survival and iii) to assess the cost-effectiveness of the experimental PET/CT scans.
Statistical methods: IMPACT-MBC aims to model the predictive value of several tests (novel molecular imaging, biopsy and blood biomarkers) in combination, by means of multivariable regression-model based techniques, combined with state-of-the-art methods for estimating the added value of novel tests to existing information (e.g. NRI, IDI). All these analyses will be employed both on (predicting responsiveness on) a patient- and metastasis level.
Present accrual and target accrual: The IMPACT-MBC trial was opened for accrual at the University Medical Center (UMC) Groningen, in August 2013. Accrual rate is as anticipated 2-3 patients/month/center. The two other participating centers, Radboud MC Nijmegen and VUmc Amsterdam recently opened. It is anticipated that accrual of patients will be finalized in 2016.
Citation Format: Frederike Bensch, Adrienne Brouwers, Andor Glaudemans, Johan de Jong, Erik de Vries, Winette van de Graaf, Eline Boon, Wim Oyen, Lioe-Fee de Geus-Oei, Eric Visser, Erik van Helden, Willemien Menke-van der Hoeven van Oordt, Henk Verheul, Otto Hoekstra, Jim Janssen, Marc Huisman, Sjoerd Elias, Carl Moons, Liesbeth de Vries, Carolien Schröder. IMPACT: IMaging PAtients for Cancer drug selecTion – Metastatic breast cancer (MBC) abstract. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr OT3-2-01.
PDF
