scholarly journals Evolutions in rectal cancer MRI staging and risk stratification in The Netherlands

Author(s):  
Nino Bogveradze ◽  
Najim el Khababi ◽  
Niels W. Schurink ◽  
Joost J. M. van Griethuysen ◽  
Shira de Bie ◽  
...  

Abstract Purpose To analyze how the MRI reporting of rectal cancer has evolved (following guideline updates) in The Netherlands. Methods Retrospective analysis of 712 patients (2011–2018) from 8 teaching hospitals in The Netherlands with available original radiological staging reports that were re-evaluated by a dedicated MR expert using updated guideline criteria. Original reports were classified as “free-text,” “semi-structured,” or “template” and completeness of reporting was documented. Patients were categorized as low versus high risk, first based on the original reports (high risk = cT3-4, cN+, and/or cMRF+) and then based on the expert re-evaluations (high risk = cT3cd-4, cN+, MRF+, and/or EMVI+). Evolutions over time were studied by splitting the inclusion period in 3 equal time periods. Results A significant increase in template reporting was observed (from 1.6 to 17.6–29.6%; p < 0.001), along with a significant increase in the reporting of cT-substage, number of N+ and extramesorectal nodes, MRF invasion and tumor-MRF distance, EMVI, anal sphincter involvement, and tumor morphology and circumference. Expert re-evaluation changed the risk classification from high to low risk in 18.0% of cases and from low to high risk in 1.7% (total 19.7%). In the majority (17.9%) of these cases, the changed risk classification was likely (at least in part) related to use of updated guideline criteria, which mainly led to a reduction in high-risk cT-stage and nodal downstaging. Conclusion Updated concepts of risk stratification have increasingly been adopted, accompanied by an increase in template reporting and improved completeness of reporting. Use of updated guideline criteria resulted in considerable downstaging (of mainly high-risk cT-stage and nodal stage). Graphic abstract

2021 ◽  
pp. 028418512110572
Author(s):  
Gustav Alvfeldt ◽  
Peter Aspelin ◽  
Lennart Blomqvist ◽  
Nina Sellberg

Background In 2014, a national workshop program was initiated and a reporting template and manual for rectal cancer primary staging using magnetic resonance imaging (MRI) was introduced and made available by the national Swedish Colorectal Cancer Registry. Purpose To evaluate the effect of the national template program by identify if there was a gap between the content in Swedish MRI reports from 2016 and the national reporting template from 2014. The aim was to explore and compare differences in content in reporting practice in different hospitals in relation to the national reporting template, with focus on: (i) identifying any implementational differences in reporting styles; and (ii) evaluating if reporting completeness vary based on such implementational differences. Material and Methods A total of 250 MRI reports from 10 hospitals in four healthcare regions in Sweden were collected. Reports were analyzed using qualitative content analysis with a deductive thematic coding scheme based on the national reporting template. Results Three different implemented reporting styles were identified with variations of content coverage in relation to the template: (i) standardized and structured protocol (reporting style A); (ii) standardized semi-structured free-text (reporting style B); and (iii) regular free-text (reporting style C). The relative completeness of reporting practice of rectal cancer staging in relation to the national reporting template were 92.9% for reporting style A, 77.5% for reporting style B, and 63.9% for reporting style C. Conclusion The implementation of template-based reporting according to reporting style A is a key factor to conform to evidence-based practice for rectal cancer reporting using MRI.


Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 5648-5648
Author(s):  
Yazan Migdady ◽  
Taiga Nishihori ◽  
Rachid Baz ◽  
Ram Thapa ◽  
Youngchul Kim ◽  
...  

Abstract Background: A commercially available gene expression profiling (GEP) model is an important risk stratification method in multiple myeloma. GEP is helpful in dividing myeloma into low and high risk based on a pre-determined threshold, however, the value of sequential GEP testing on patients receiving sequential anti-myeloma therapies has yet to be fully determined. Methods: Fifty four myeloma patients at Moffitt Cancer Center underwent two sequential GEPs based a dedicated 70-gene panel using an Affymetrixmicroarray platform (MyPRSTM) from bone marrow aspirate samples during the course of their disease. Myeloma was characterized based on the risk classification (cutoff of score 45.2), risk score (0-100), differences in the score/classification, and molecular subtyping. Pearson correlation analysis was performed to correlate GEP scores at two time points. Overall survival (OS) was estimated using the Kaplan-Meier method from the time of first GEP analysis and OS curves were compared using the log-rank test. Multivariate Cox proportional hazards regression models were built for OS. Results: Majority were male (67%) and hadDurie-Salmon stage 2 or 3 disease (83%).Immunophenotypeswere IgG (56%), IgA (22%) and light chain (20%). At first GEP testing (Time 1), 20% (11/54) were high risk and the median score was 28.6 (range, 10.8-66.5) with frequency of molecular subtypes being cycle family (CD) 1&2 28%,hyperdiploidy(HY) 24%, low bone disease (LB) 22%, proliferation (PR) 17%, and MMSET associated (MS) 9%. There were no MAF associated cases in this cohort. At second GEP testing (Time 2), 28% (15/54) were high risk with a median score of 33.5 (range, 11.4-96.3). Pearson correlation coefficient for the GEP scores of Times 1 & 2 was r=0.77 (p<0.001). Risk group for eight patients (15%) changed with 6 moving from low to high risk and 2 with high to low risk. Molecular subtype for 18 patients (33%) changed with most frequent pattern being LB to PR (n=5) followed by PR to LB (n=3). Median OS for the entire group was 21.4 months. In this cohort, there were no statistical differences in OS based on risk stratification at Time 1 (p=0.187, log-rank), change in risk stratification (p=0.131), and molecular subtypes at Time 1 (p=0.09). When this cohort of patients was re-categorized based on the median GEP score (28.58), OS was significantly worse for those with scores higher than the median (n=27 (50%), p<0.001). With a new cutoff value of 30, patients with a GEP score≥ 30 had inferior OS either based on first GEP (Time 1; n=24 (44%), p=0.02; Figure 1) or second (Time 2; n=33 (61%), p=0.04; Figure 2). With the cutoff value of 30 as a new threshold, patients who had high scores for both Times 1 and 2 (n=24) had worse OS compared to those with both low scores (n=21) and those moved from low to high scores (n=9: p=0.017). When patients with GEP score differences between Times 1 and 2 of more than 1 standard deviation (n=4 moving from low to high with a total n=12) were compared to the rest, there were no statistical differences in OS (p=0.296). In multivariate analyses using the GEP score, score difference, molecular subtype and risk classification, GEP score was the only significant predictive factor for inferior OS (hazard ratio 1.1, 95% confidence interval:1.03-1.18, p=0.006). Conclusions: Serial GEP analysis on myeloma patients demonstrates longitudinal changes in risk scores, molecular subtyping and risk classification suggesting clonal evolution or modifications of overall transcribed genetic signature with systemic therapy. GEP risk score may potentially provide graded risk assessment rather than dichotomous categorization as different risk threshold may be found based on observation of a new cutoff value predictive of OS. Further analysis of gene expression patterns is ongoing to elucidate risk stratification based on molecular signatures and to elucidate potential treatment associated profiles. Figure 1 Figure 1. Disclosures Nishihori: Novartis: Research Funding; Signal Genetics: Research Funding. Baz:Novartis: Research Funding; Millennium: Research Funding; Merck: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Signal Genetics: Research Funding; Karyopharm: Research Funding; Bristol-Myers Squibb: Research Funding. Van Laar:Signal Genetics, Inc.: Employment. Bender:Signal Genetics, Inc.: Employment. Alsina:Takeda/Millennium: Research Funding; Novartis: Research Funding; Signal Genetics: Consultancy; Amgen/Onyx: Consultancy, Speakers Bureau. Shain:Takeda/Millennium: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Signal Genetics: Research Funding; Amgen/Onyx: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Novartis: Speakers Bureau.


Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 1765-1765
Author(s):  
Srdan Verstovsek ◽  
Jingbo Yu ◽  
Jonathan K. Kish ◽  
Dilan Chamikara Paranagama ◽  
Jill Kaufman ◽  
...  

Abstract Introduction Myelofibrosis (MF) is a myeloproliferative neoplasm characterized by marrow fibrosis, extramedullary hematopoiesis, and leukoerythroblastosis. Clinical manifestations include severe anemia, splenomegaly, and symptoms. Median survival in patients with primary MF ranges from 2 to 11 years, depending on risk categorization. The National Comprehensive Cancer Network (NCCN) Clinical Practice Guidelines recommend the International Prognostic Scoring System (IPSS) for risk stratification at diagnosis; other systems including the Dynamic IPSS (DIPSS) and the DIPSS-Plus are also cited in the Guidelines. Treatment recommendations are risk-adapted in the NCCN Guidelines. The objective of this study is to describe how patients are risk stratified at diagnosis by community hematologists/oncologists and the impact that risk stratification has on the initiation of MF-directed treatments. Methods Medical chart reviews were conducted at community hematology/oncology practices in the OPEN network. Adult patients diagnosed with primary MF, post-PV MF, or post-ET MF between 1/2012 and 12/2016 and receiving care for at least 6 months were included. Data were collected with an electronic case report form (eCRF) with questions on clinical characteristics (symptoms, Hgb, WBC, blast %, and PLT) and risk assessment method used at diagnosis (IPSS, DIPSS, or DIPSS-Plus), treatments, and outcomes. A data-derived IPSS risk score was calculated for each patient. To assess the accuracy of the assigned risk, a data-derived risk score, corresponding to the system used by the provider, was also calculated. Patients were classified as treated at diagnosis if they received MF-directed therapy (hydroxyurea, interferon, ruxolitinib, or clinical trial) or allogeneic hematopoietic cell transplant (HCT) within 120 days of diagnosis. The methods and rates of risk stratification, accuracy of the provider-assigned risk versus data-derived risk, and treatment administered were reported. Results A total of 338 patients with MF from 28 community hematology/oncology practices were included. Mean (SD) age at diagnosis was 65.3 (11.8) years, 51.8% were male, and 68.3% had primary MF. JAK2, MPL, and CALR mutations were tested in 86.1%, 70.1%, and 60.9% of patients at diagnosis, of these, 71.1%, 23.2%, and 14.6% were positive, respectively; 18.4% (38/206) were triple negative. Median follow-up from diagnosis was 27.5 months (IQR, 18.5-42.6). Approximately 32% of patients did not have a risk classification in their medical records at diagnosis. A scoring system was used for risk assignment in 45.3% of patients; DIPSS (23.0%) and IPSS (21.3%) were most commonly used. Of all 338 patients, the corresponding data-derived risk classifications were: 5.6% low, 20.1% int-1, 18.3% int-2, and 55.9% high risk. Among those patients who were not assigned risk by their treating physicians (n=108), most had int-1 (28.7%), int-2 (17.6%), or high risk (43.5%) disease based on the data-derived IPSS risk classification. Of those who received a risk classification from their treating physician, 47.4% (n=109) received an inaccurate risk classification; among these patients, the risk was under-estimated for most (82.6%) (Table 1). Overall, 55.8% of patients (63.2% low-risk, 55.9% int-1, 52.5% int-2, 56.1% high-risk) received MF-directed pharmacological treatment or HCT within 4 months of diagnosis. Among all patients receiving MF-directed treatment, the mean time from diagnosis to treatment initiation was 5.3 months (SD=1.8), and the most common first pharmacological treatments were ruxolitinib (49.8%) and hydroxyurea (46.7%). Splenomegaly (81.3%), symptoms (72.6%), and anemia (65.6%) were top cited indications for treatment initiation. The treatment initiation rate was higher among those patients correctly risk classified compared to those incorrectly classified (64.2% versus 49.5%, p=0.032). Conclusions Nearly one-third of patients with MF did not receive a risk classification at diagnosis. When risk was assigned, almost half were incorrectly classified. Just over half of patients received treatment within four months of diagnosis. Patients who were correctly risk classified at diagnosis were more likely to start treatment promptly upon diagnosis versus those incorrectly risk classified, which may be attributable to the under-estimation of risk. Disclosures Verstovsek: Celgene: Membership on an entity's Board of Directors or advisory committees; Incyte: Consultancy; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Italfarmaco: Membership on an entity's Board of Directors or advisory committees. Yu:Incyte Corporation: Employment, Equity Ownership. Kish:Cardinal Health: Employment. Paranagama:Incyte: Employment, Equity Ownership. Kaufman:Cardinal Health: Employment. Chung:Cardinal Health: Employment. Grunwald:Genentech: Research Funding; Incyte Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Agios: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; Alexion: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Medtronic: Equity Ownership; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cardinal Health: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Consultancy, Membership on an entity's Board of Directors or advisory committees; Ariad: Consultancy, Membership on an entity's Board of Directors or advisory committees; Forma Therapeutics: Research Funding. Colucci:Incyte: Employment, Equity Ownership. Mesa:UT Health San Antonio - Mays Cancer Center: Employment; NS Pharma: Research Funding; Promedior: Research Funding; Gilead: Research Funding; Incyte Corporation: Research Funding; CTI Biopharma: Research Funding; Genentech: Research Funding; Celgene: Research Funding; Novartis: Consultancy; Pfizer: Research Funding.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Thomas Sonnweber ◽  
Eva-Maria Schneider ◽  
Manfred Nairz ◽  
Igor Theurl ◽  
Günter Weiss ◽  
...  

Abstract Background Risk stratification is essential to assess mortality risk and guide treatment in patients with precapillary pulmonary hypertension (PH). We herein compared the accuracy of different currently used PH risk stratification tools and evaluated the significance of particular risk parameters. Methods We conducted a retrospective longitudinal observational cohort study evaluating seven different risk assessment approaches according to the current PH guidelines. A comprehensive assessment including multi-parametric risk stratification was performed at baseline and 4 yearly follow-up time-points. Multi-step Cox hazard analysis was used to analyse and refine risk prediction. Results Various available risk models effectively predicted mortality in patients with precapillary pulmonary hypertension. Right-heart catheter parameters were not essential for risk prediction. Contrary, non-invasive follow-up re-evaluations significantly improved the accuracy of risk estimations. A lack of accuracy of various risk models was found in the intermediate- and high-risk classes. For these patients, an additional evaluation step including assessment of age and right atrium area improved risk prediction significantly. Discussion Currently used abbreviated versions of the ESC/ERS risk assessment tool, as well as the REVEAL 2.0 and REVEAL Lite 2 based risk stratification, lack accuracy to predict mortality in intermediate- and high-risk precapillary pulmonary hypertension patients. An expanded non-invasive evaluation improves mortality risk prediction in these individuals.


Vaccines ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 144
Author(s):  
Florian Zeevat ◽  
Evgeni Dvortsin ◽  
Abrham Wondimu ◽  
Jan C. Wilschut ◽  
Cornelis Boersma ◽  
...  

In this study, we estimated the benefits of rotavirus vaccination for infants had the rotavirus vaccine been introduced in the Netherlands as of its market authorization in 2006. An age-structured, deterministic cohort model was developed to simulate different birth cohorts over a period of 15 years from 2006 until 2021, comparing both universal and targeted high-risk group vaccination to no vaccination. Different scenarios for the duration of protection (5 or 7 years) and herd immunity (only for universal vaccination) were analyzed. All birth cohorts together included 2.6 million infants, of which 7.9% were high-risk individuals, and an additional 13.2 million children between 1–15 years born prior to the first cohort in 2006. The costs and health outcomes associated with rotavirus vaccination were calculated per model scenario and discounted at 4% and 1.5%, respectively. Our analysis reveals that, had rotavirus vaccination been implemented in 2006, it would have prevented 356,800 (51% decrease) and 32,200 (5% decrease) cases of rotavirus gastroenteritis after universal and targeted vaccination, respectively. Over the last 15 years, this would have led to significant avoided costs and quality-adjusted life year losses for either vaccination strategy with the most favorable outcomes for universal vaccination. Clearly, an opportunity has been lost.


Open Heart ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. e001459
Author(s):  
Jelle C L Himmelreich ◽  
Wim A M Lucassen ◽  
Ralf E Harskamp ◽  
Claire Aussems ◽  
Henk C P M van Weert ◽  
...  

AimsTo validate a multivariable risk prediction model (Cohorts for Heart and Aging Research in Genomic Epidemiology model for atrial fibrillation (CHARGE-AF)) for 5-year risk of atrial fibrillation (AF) in routinely collected primary care data and to assess CHARGE-AF’s potential for automated, low-cost selection of patients at high risk for AF based on routine primary care data.MethodsWe included patients aged ≥40 years, free of AF and with complete CHARGE-AF variables at baseline, 1 January 2014, in a representative, nationwide routine primary care database in the Netherlands (Nivel-PCD). We validated CHARGE-AF for 5-year observed AF incidence using the C-statistic for discrimination, and calibration plot and stratified Kaplan-Meier plot for calibration. We compared CHARGE-AF with other predictors and assessed implications of using different CHARGE-AF cut-offs to select high-risk patients.ResultsAmong 111 475 patients free of AF and with complete CHARGE-AF variables at baseline (17.2% of all patients aged ≥40 years and free of AF), mean age was 65.5 years, and 53% were female. Complete CHARGE-AF cases were older and had higher AF incidence and cardiovascular comorbidity rate than incomplete cases. There were 5264 (4.7%) new AF cases during 5-year follow-up among complete cases. CHARGE-AF’s C-statistic for new AF was 0.74 (95% CI 0.73 to 0.74). The calibration plot showed slight risk underestimation in low-risk deciles and overestimation of absolute AF risk in those with highest predicted risk. The Kaplan-Meier plot with categories <2.5%, 2.5%–5% and >5% predicted 5-year risk was highly accurate. CHARGE-AF outperformed CHA2DS2-VASc (Cardiac failure or dysfunction, Hypertension, Age >=75 [Doubled], Diabetes, Stroke [Doubled]-Vascular disease, Age 65-74, and Sex category [Female]) and age alone as predictors for AF. Dichotomisation at cut-offs of 2.5%, 5% and 10% baseline CHARGE-AF risk all showed merits for patient selection in AF screening efforts.ConclusionIn patients with complete baseline CHARGE-AF data through routine Dutch primary care, CHARGE-AF accurately assessed AF risk among older primary care patients, outperformed both CHA2DS2-VASc and age alone as predictors for AF and showed potential for automated, low-cost patient selection in AF screening.


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