Investigation of a 22-gene genomic classifier (GC) for risk stratification and molecular subtyping in an Asian prostate cancer (PCa) cohort.

2021 ◽  
Vol 39 (6_suppl) ◽  
pp. 249-249
Author(s):  
Wei Loong Sherman Yee ◽  
Wai Yee Woo ◽  
Adelene Sim ◽  
Kar Perng Low ◽  
Alice Meng ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Stratification ◽  
Racial Differences ◽  
White Men ◽  
Risk Groups ◽  
Molecular Subtyping ◽  
Basal Subtype ◽  
Grid Database ◽  
Risk Patients ◽  
Very High

249 Background: A 22-gene GC has been proposed to refine risk stratification of localized PCa by conventional NCCN criteria, and this may potentially influence treatment recommendations. Nonetheless, majority of studies looking at the utility of GC were conducted in White and non-White men from Western cohorts. We therefore investigated the association of GC with NCCN risk groups (RG) in an Asian PCa cohort. Additionally, we examined for inter-racial differences in molecular subtyping between Asian and White/non-White PCa. Methods: GC (Decipher Biosciences Inc., CA) was performed on diagnostic biopsies of men who were treated with radiotherapy +/- hormonal therapy at a single institution (N = 75). ISUP Gleason’s grade (GG) and tumor cellularity were reviewed by an expert GU pathologist. RNA was extracted from 2 x 2.0-mm tumor cores using Qiagen AllPrep DNA/RNA FFPE Kit (Qiagen, Germany) and gene expression was performed on Affymetrix Human Exon 1.0 ST Array (ThermoFischer, CA). PAM50 molecular subtyping was derived using the DecipherGRID database. Results: We profiled 80 tumors from 75 patients, comprising of 18 (24.0%), 9 (12.0%), 21 (28.0%), and 19 (25.3%) NCCN low-/favorable intermediate-, unfavorable intermediate-, high- and very high-RG, respectively; of note, 8 (10.7%) patients had regional/metastatic disease at diagnosis. Using the GC, 27 (33.8%), 14 (17.5%) and 39 (48.8%) were classified as low- (<0.45), intermediate- (0.45-0.6) and high-RG, respectively (>0.6). When stratified using a three-tier clinico-genomic (CG) classification system (Spratt et al. 2017), 6 of 21 (28.6%) NCCN-defined high-risk and 4 of 19 (21.1%) very high-risk patients were downgraded to CG-defined intermediate-/low-risk, while 2 of 27 (7.4%) NCCN low-/intermediate-risk patients were in fact upgraded to CG high-risk. Next, we interrogated the PAM50 basal-luminal signature in our cohort. Interestingly, when matched to White (N = 5762) and non-White (N = 155) for NCCN RG, ISUP GG and age, we observed a high proportion of basal subtype (62.7%) in Asians, which contrasted the prevalence observed in White (16.7%) and non-White (15.9%) North American patients (Chi-sq P <0.001). Conclusions: Here, we demonstrated the utility of the 22-gene GC for refining the NCCN risk stratification in a largest Asian PCa dataset to-date. An unexpectedly high proportion of PAM50 basal-subtype was observed, suggesting race-specific differences of the tumor transcriptome.

Abstract P275: Demographic and Clinical Profile of Patients with Risk Factors for Coronary Heart Disease (CHD) Defined by National Cholesterol Education Program (NCEP) Adult Treatment Panel (ATP) III Guidelines

Circulation ◽  
2014 ◽  
Vol 129 (suppl_1) ◽  
Author(s):  
David M Kern ◽  
Sanjeev Balu ◽  
Ozgur Tunceli ◽  
Swetha Raparla ◽  
Deborah Anzalone
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
Risk Groups ◽  
Lipid Lowering ◽  
High Risk Patients ◽  
Low Hdl ◽  
Risk Patients ◽  
Artery Disease ◽  
Very High ◽  
Statin Use

Introduction: This study aimed to compare the demographic and clinical characteristics of patients with different risk factors for CHD as defined by NCEP ATP III guidelines. Methods: Dyslipidemia patients (≥1 medical claim for dyslipidemia, ≥1 pharmacy claim for a statin, or ≥1 LDL-C value ≥100 mg/dL [index date]) aged ≥18 y were identified from the HealthCore Integrated Research Environment from 1/1/2007-7/31/2012. Patients were classified as low risk (0 or 1 risk factor): hypertension, age ≥45 y [men] or ≥55 y [women], or low HDL-C), moderate/moderately high risk (≥2 risk factors), high risk (having CHD or CHD risk equivalent), or very high risk (having ACS or other established cardiovascular disease plus diabetes or metabolic syndrome). Demographics, comorbidities, medication use and lipid levels during the 12 months prior, and statin use during the 6 months post-index date were compared across risk groups (very high vs each other risk group). Results: There were 1,524,351 low-risk (mean age: 47 y; 45% men), 242,357 moderate-risk (mean age: 58 y; 59% men), 188,222 high-risk (mean age: 57 y; 52% men), and 57,469 very-high-risk (mean age: 63 y; 61% men) patients identified. Mean Deyo-Charlson comorbidity score differed greatly across risk strata: 0.20, 0.33, 1.26, and 2.22 from low to very high risk (p<.0001 for each). Compared with high-risk patients, very-high-risk patients had a higher rate of ischemic stroke: 5.4% vs 4.1%; peripheral artery disease: 17.1% vs 11.6%; coronary artery disease: 8.5% vs 8.2%; and abdominal aortic aneurysm: 2.3% vs 2.0% (p<.05 for each). Less than 1% of the total population had a prior prescription for each non-statin lipid-lowering medication (bile acid sequestrants, fibrates, ezetimibe, niacin, and omega-3). Very-high-risk patients had lower total cholesterol (very-high-risk mean: 194 mg/dL vs 207, 205, and 198 mg/dL for low-, moderate-/moderately-high-, and high-risk patients, respectively) and LDL-C (very-high-risk mean: 110 mg/dL vs 126, 126, and 116 mg/dL for the other risk groups; p<.0001 for each); higher triglycerides (TG) (very-high-risk mean: 206 mg/dL vs 123, 177, and 167 mg/dL for the other groups; p<.0001 for each); and lower HDL-C (very-high-risk mean: 45 mg/dL vs 57 [p<.0001], 45 [p=.006], and 51 mg/dL [p<.0001]). Statin use was low overall (15%), but higher in the very-high-risk group (45%) vs the high- (29%), moderate-/moderately-high- (18%), and low- (12%) risk groups (p<.0001 for each). Conclusions: Despite a large proportion of patients having high lipid levels, statin use after a dyslipidemia diagnosis was low: ≥80% of all patients (and more than half at very high risk) failed to receive a statin, indicating a potentially large population of patients who could benefit from statin treatment. Prior use of non-statin lipid-lowering medications was also low considering the high TG and low HDL-C levels among high-risk patients.

scholarly journals Comparação da Aplicação da EER Hema-Obs a 250 Gestações da Consulta de Hematologia-Obstetrícia do Centro Hospitalar São João, Portugal Versus EER Galit Sarig a 90 Gestações no Rambam Health Care Campus, Israel

2015 ◽  
Vol 28 (2) ◽  
pp. 189
Author(s):  
Ana Salselas ◽  
Inês Pestana ◽  
Francisco Bischoff ◽  
Mariana Guimarães ◽  
Joaquim Aguiar Andrade
Keyword(s):  
High Risk ◽  
Risk Stratification ◽  
Pregnant Women ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Risk Groups ◽  
Low Risk ◽  
Very High ◽  
Receiver Operating

<strong>Introduction:</strong> Pregnant women with thromboembolic diseases, previous thrombotic episodes or thrombophilia family history were supervised in a multidisciplinary Obstetrics/ Hematology consultation in Centro Hospitalar São João EPE, Porto, Portugal. For the evaluation and medication of these women, a risk stratification scale was used.<br /><strong>Purposes:</strong> The aim of this study was to validate a Risk Stratification Scale and thromboprophylaxis protocol by means of comparing it with a similar scale, developed and published by Sarig.<br /><strong>Material and Methods:</strong> We have compared: The distribution, by risk groups, obtained through the application of the two scales on pregnant women followed at Centro Hospitalar São João, Porto, Portugal, consultation; the sensibility and specificity for each one of the scales (DeLong scale, applied to Receiver Operating Characteristic) curves; the outcomes in pregnancies followed in Hospital São João, Porto, Portugal<br /><strong>Results:</strong> According to our Hema-Obs risk stratification scale, 29% were allocated to low-risk, 47% to high-risk and 24% to very-high-risk groups. According to Galit Sarig risk stratification scale, 24% were considered low-risk, 53% moderate, 16% high-risk and 7% as very high-risk group. In our study we observed 9% of spontaneous abortions, in comparison with 18% in the Galit Sarig cohort. From the application of Receiver Operating Characteristic curve to both risk stratification scales, the results of the calculated areas were 58,8% to our Hema-Obs risk stratification scale and 38,7% to Galit Sarig risk stratification scale, with a Delong test significancie of p = 0.0006.<br /><strong>Conclusions:</strong> We concluded that Hema-Obs risk stratification scale is an effective support for clinical monitoring of therapeutic strategies.

Survival in Patients with Newly Diagnosed Myeloma Undergoing Therapy with Lenalidomide and Dexamethasone: Impact of High-Risk Cytogenetic Risk Status on Outcome

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 95-95 ◽  
Author(s):  
Prashant Kapoor ◽  
Shaji Kumar ◽  
Rafael Fonseca ◽  
Martha Q. Lacy ◽  
Thomas E Witzig ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Stratification ◽  
Plasma Cell ◽  
Risk Groups ◽  
Newly Diagnosed ◽  
High Risk Patients ◽  
Risk Patients ◽  
The Impact ◽  
Standard Risk

Abstract Background: Multiple myeloma (MM) is a heterogeneous disease with very divergent outcomes that are dictated in a large part by specific cytogenetic abnormalities, as well as other prognostic factors such as the proliferative rate of marrow plasma cells. Prognostic systems incorporating these factors have shown clinical utility in identifying high-risk patients, and are increasingly being utilized for treatment decision-making. However, the prognostic relevance of these factors may change with the application of novel therapies. The objective of this study was to determine the impact of risk-stratification (incorporating plasma cell metaphase cytogenetics, interphase fluorescent in-situ hybridization (FISH) and the slide-based plasma cell labeling index (PCLI)) in a cohort of patients with newly diagnosed MM treated initially with lenalidomide + dexamethasone (Rev-Dex). Methods: From March 2004 to November 2007, 100 consecutive patients treated with Rev (25mg/day) on days 1 through 21 of a 4-week cycle in combination with dexamethasone as initial therapy for newly diagnosed myeloma, were identified. High-risk MM was defined as presence of any one or more of the following: hypodiploidy, monoallelic loss of chromosome 13 or its long arm (by metaphase cytogenetics only), deletion of p53 (locus 17p13) or PCLI ≥ 3% or immunoglobulin heavy chain (IgH) translocations, t(4;14) (p16.3;q32) or t(14;16)(q32;q23) on FISH. PFS and OS survival estimates were created using the Kaplan Meier method, and compared by log-rank tests. Results: The median estimated follow-up of the entire cohort (N=100) was 36 months. The median PFS was 31 months; the median OS has not been reached. The 2- and 3-year OS estimates were 93% and 83%, respectively. 16% patients were deemed high-risk by at least one of the 3 tests (cytogenetics, FISH or PCLI). Response rates (PR or better) were 81% versus 89% in the high-risk and standard risk groups, respectively, P=NS; corresponding values for CR plus VGPR rates were 38% and 45% respectively. The median PFS was 18.5 months in high-risk patients compared to 37 months in the standard-risk patients (n=84), P<0.001(Figure). Corresponding values for TTP were 18.5 months and 36.5 months, respectively, P=<0.001. OS was not statistically significant between the two groups; 92% 2-year OS was noted in both the groups. Overall, 95 patients had at least one of the 3 tests to determine risk, while 55 patients could be adequately stratified based on the availability of all the 3 tests, or at least one test result that led to their inclusion in the high-risk category. The significant difference in PFS persisted even when the analysis was restricted to the 55 patients classified using this stringent criterion; 18.5 months vs. 36.5 months in the high-risk and standard- risk groups respectively; P<0.001. In a separate analysis, patients who underwent SCT before the disease progression were censored on the date of SCT to negate its effect, and PFS was still inferior in the high-risk group (p=0.002). Conclusion: The TTP and PFS of high-risk MM patients are inferior to that of the standard-risk patients treated with Rev-Dex, indicating that the current genetic and proliferation-based risk-stratification model remains prognostic with novel therapy. However, the TTP, PFS, and OS obtained in high-risk patients treated with Rev-Dex in this study is comparable to overall results in all myeloma patients reported in recent phase III trials. In addition, no significant impact of high-risk features on OS is apparent so far. Longer follow-up is needed to determine the impact of risk stratification on the OS of patients treated with Rev-Dex. Figure Figure

Clinical-genomic sub-classification of high-risk prostate cancer: Implications for tailoring therapy and clinical trial design.

2020 ◽  
Vol 38 (6_suppl) ◽  
pp. 337-337
Author(s):  
Vinayak Muralidhar ◽  
Mohammed Alshalalfa ◽  
Daniel Eidelberg Spratt ◽  
Yang Liu ◽  
R. Jeffrey Karnes ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
High Risk ◽  
Risk Stratification ◽  
High Risk Prostate Cancer ◽  
High Risk Disease ◽  
Risk Prostate Cancer ◽  
Risk Patients ◽  
Genomic Risk ◽  
Clinical Genomic ◽  
Very High

337 Background: Current risk stratification schema have limited prognostic performance in predicting outcome within National Comprehensive Cancer Network (NCCN) high-risk to very high-risk prostate cancer. Methods: Two multicenter high-risk cohorts were used for training (n = 214) and validation (n = 151) of a novel RNA microarray-based integrated clinical-genomic Classifier Optimized for Outcome in High-risk Prostate cancer (COOHP) to classify patients as COOHP favorable high-risk, standard high-risk, or very high-risk. Cox analysis was used to model metastasis-free survival (MFS), prostate cancer-specific survival (PCSS), and overall survival (OS). Model performance was compared to prior sub-classification systems using time-dependent c-indices. Results: Among NCCN high/very high-risk patients in the training cohort, 11% were classified as COOHP favorable high-risk, 70% as COOHP standard high-risk, and 18% as COOHP very high-risk. Patients with COOHP favorable high-risk disease had better rates of 5-year MFS compared to those with COOHP standard high-risk disease (94% vs 76%, hazard ratio [HR] 0.10, p = 0.02), and patients with COOHP very high-risk disease had worse 5-year MFS compared to those with COOHP standard high-risk disease (34% vs 76%, HR 3.5, p < 0.0001). Similarly, patients with COOHP very high-risk disease had worse 10-year PCSS compared to those with COOHP standard high-risk disease (36% vs 82%, HR 4.4, p < 0.0001). The c-indices for 5-year MFS and 10-year PCSS in the training cohort were 0.80 and 0.74, significantly improved compared to prior clinical and clinical-genomic risk stratification systems (0.62-0.69 for 5-year MFS and 0.56-0.63 for 10-year PCSS). These results were consistent in the validation cohort, where 5-year MFS significantly varied among the three COOHP subgroups (100% vs 89% vs 79%, p = 0.020), as did 10-year OS (100% vs 71% vs 53%, p = .040). Conclusions: A clinical-genomic risk stratification system specifically designed to discriminate prognosis in high-risk prostate cancer better identified favorable high-risk and very high-risk subsets of disease compared to prior clinical and clinical-genomic stratification systems.

scholarly journals Dropping risk stratification with subsequent treatment-risk paradox in non ST elevation acute coronary syndromes: a clinical audit in Iraq

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zainab Atiyah Dakhil ◽  
Hasan Ali Farhan
Keyword(s):  
Chest Pain ◽  
High Risk ◽  
Risk Stratification ◽  
Cardiogenic Shock ◽  
Risk Scores ◽  
Treatment Risk ◽  
Risk Patients ◽  
Coronary Syndromes ◽  
Very High ◽  
Risk Categories

Abstract Background Risk stratification is the cornerstone in managing patients with Non-ST Elevation Acute Coronary Syndromes (NSTE-ACS) and can attenuate the unjustified variability in treatment and guide the intervention decision notwithstanding its impact on better healthcare resources use. This study sought to disclose real adherence to guidelines in risk stratification of NSTE-ACS patients and in adopting intervention decision in practice. Methods Multicentre prospective study recruited NSTE-ACS patients. Baseline characteristics were collected, TIMI (Thrombolysis in Myocardial Infarction) and GRACE (Global Registry of Acute Coronary Events) scores were calculated, management strategy as well as timing to intervention were recorded. Results n. = 150, 72% of them were males, mean age was (59 ± 12.32) years. TIMI score was calculated in 5.3% of patients with none of them had GRACE score calculated. Invasive strategy was adopted in 85.24 and 82.7% of low GRACE and TIMI risk categories respectively, while invasive approach used in 42.85 and 40% of high GRACE and TIMI risk categories respectively. The immediate intervention in less than 2 hours was more to be used in low-risk categories while the high-risk and very high-risk patients whom were managed invasively were catheterized within >72 h; or more frequently to be non-catheterized at all. Sixty percent of those with acute heart failure, 80.76% of those with ongoing chest pain, 85% of those with dynamic ST changes same as 80% of those with cardiogenic shock were treated conservatively. Using multivariable analysis older age, ongoing chest pain and cardiogenic shock predicted conservative approach. Conclusions There is striking underuse of risk scores in practice that can contribute to treatment-risk paradox in managing NSTE-ACS in form of depriving those with higher risk from invasive strategy despite being the most beneficiaries. The paradox did not only involve the very high-risk patients but also the very high-risk criteria like ongoing chest pain and cardiogenic shock predicted conservative approach, this highlights that the entire approach to patients with NSTE-ACS should be reconsidered, regardless of the use of risk scores in clinical practice. Audit programs activation in middle eastern countries can inform policymakers to put a limit to the treatment-risk paradox for better cardiovascular care and outcomes.

scholarly journals Patients Risk Stratification in the Management of Osteoporosis: the Latest International Guidelines

2021 ◽  
Vol 47 (3) ◽  
pp. 8-16
Author(s):  
Siok Bee Chionh
Keyword(s):  
High Risk ◽  
Risk Stratification ◽  
Fragility Fracture ◽  
Pharmacological Agent ◽  
Oral Bisphosphonates ◽  
Moderate Risk ◽  
International Guidelines ◽  
Anabolic Agent ◽  
Risk Patients ◽  
Very High

Assessment of risk of a fragility fracture is a vital step a physician needs to undertake in every patient suspected of osteoporosis, as this will influence the decisions on whether to treat with a pharmacological agent, with which drug, and for how long. After risk stratification, patients deemed Very High-Risk should be considered for an anabolic agent, or if this is not feasible, a parenteral anti-resorptive. High- Risk or Moderate-Risk patients may be considered for oral bisphosphonates.

Treatment decisions and outcomes for NCCN favorable intermediate-risk prostate cancer patients after receiving the 17-gene genomic prostate cancer score result.

2021 ◽  
Vol 39 (6_suppl) ◽  
pp. 218-218
Author(s):  
Eric Margolis ◽  
John Bennett ◽  
Marina Pavlova ◽  
Kenny Wong ◽  
Christopher Michael Pieczonka ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
High Risk ◽  
Risk Stratification ◽  
Multimodal Therapy ◽  
Clinical Stage ◽  
Risk Groups ◽  
Intermediate Risk ◽  
Risk Prostate Cancer ◽  
Risk Patients ◽  
To Receive

218 Background: Molecular assays are used to improve risk stratification in prostate cancer. This study determined how the 17-gene Genomic Prostate Score (GPS) assay guides treatment decisions in patients with NCCN favorable intermediate-risk prostate cancer. Methods: This retrospective study included 324 patients from 7 urology practices in the United States. All patients had NCCN favorable intermediate-risk prostate cancer, defined as <50% positive biopsy cores and only one of the following risk factors: grade group 2 (Gleason Score 3+4), clinical stage T2b-T2c, or PSA 10-20 ng/mL. All patients also had a GPS assay report dated May 2017 to April 2019. The GPS assay allows risk stratification into post-GPS very low-, low-, favorable intermediate-, unfavorable intermediate-, and high-risk groups, with higher GPS scores representing increased risk. Data were collected from patients' charts/electronic health records. The proportion of patients who selected active surveillance (AS) over immediate definitive treatment and AS, monotherapy, or multimodal therapy was calculated with 95% confidence intervals (CI) using the Clopper-Pearson method. Results: Patients comprised 79% with Gleason Score 3+4, 19% with PSA 10-20 ng/mL, and 2% with clinical stage T2b; median GPS result was 26. Post-GPS risk groups were 0%, 16%, 11%, 57%, and 16% very low-, low-, favorable intermediate-, unfavorable intermediate-, and high-risk groups respectively. Overall, 31% (95% CI 26%, 36%) of patients selected active surveillance (AS), with rate declining as post-GPS risk increased: 57% (95% CI 42%, 71%) selected AS in the post-GPS low-risk, 51% (95% CI 34%, 69%) in the post-GPS favorable intermediate-risk, 26% (95% CI 20%, 33%) in the post-GPS unfavorable intermediate-risk, and 6% (95% CI 1%, 16%) in the post-GPS high-risk group. Post-GPS unfavorable intermediate/high risk-patients were more likely to receive monotherapy than low/favorable intermediate-risk patients (high, 72%; unfavorable intermediate, 64%; favorable intermediate, 37%; and low, 37%); high-risk patients were more likely to receive multimodal therapy (high, 23%; unfavorable intermediate, 10%; favorable intermediate, 11%; and low, 6%). Median follow-up time was 18 months, and one prostate cancer-related metastasis and 2 deaths (neither prostate cancer-related) were reported. Complications (erectile dysfunction, urinary/bowel incontinence) were more common in treated than AS patients. AS persistence was 91% (95% CI 82%, 95%) at 12 months; patients discontinued AS due to disease progression (61%) or patient preference/unknown reasons (39%). Conclusions: The GPS result is associated with selection of AS and treatment intensity in this first examination of genomic classifiers in a cohort of prostate cancer patients with NCCN favorable intermediate-risk.

Have we learnt all from Improve-It? Part I. Core results and subanalyses on the effects of ezetimibe added to statin therapy related to age, gender and selected chronic diseases (kidney disease, diabetes mellitus and non- alcoholic fatty liver disease)

2020 ◽  
Vol 18 ◽  
Author(s):  
Zlatko Fras ◽  
Dimitri P. Mikhailidis
Keyword(s):  
Diabetes Mellitus ◽  
Liver Disease ◽  
High Risk ◽  
Kidney Disease ◽  
Fatty Liver ◽  
Fatty Liver Disease ◽  
Alcoholic Fatty Liver ◽  
Risk Patients ◽  
Very High ◽  
Alcoholic Fatty Liver Disease

: IMPROVE-IT (IMProved Reduction of Outcomes: Vytorin Efficacy International Trial) was a randomized clini- cal trial (18,144 patients) that evaluated the efficacy of the combination of ezetimibe with simvastatin vs simvastatin mono- therapy in patients with acute coronary syndrome (ACS) and moderately increased low-density lipoprotein cholesterol (LDL-C) levels (of up to 2.6-3.2 mmol/L; 100-120 mg/dL). After 7 years of follow-up, combination therapy resulted in an additional LDL-C decrease [1.8 mmol/L, or 70 mg/dL, within the simvastatin (40 mg/day) monotherapy arm and 1.4 mmol/L, or 53 mg/dL for simvastatin (40 mg/day) + ezetimibe (10 mg/day)] and showed an incremental clinical benefit (composite of cardiovascular death, nonfatal myocardial infarction, unstable angina requiring rehospitalization, coronary re- vascularization (≥30 days after randomization), or nonfatal stroke; hazard ratio (HR) of 0.936, and 95% CI 0.887-0.996, p=0.016). Therefore, for very high cardiovascular risk patients “even lower is even better” regarding LDL-C, independently of the LDL-C reducing strategy. These findings confirm ezetimibe as an option to treat very-high-risk patients who cannot achieve LDL-C targets with statin monotherapy. Additional analyses of the IMPROVE-IT (both prespecified and post-hoc) include specific very-high-risk subgroups of patients (those with previous acute events and/or coronary revascularization, older than 75 years, as well as patients with diabetes mellitus, chronic kidney disease or non-alcoholic fatty liver disease). The data from IMPROVE-IT also provide reassurance regarding longer-term safety and efficacy of the intensification of li- pid-lowering therapy in very-high-risk patients resulting in very low LDL-C levels. We comment on the results of several (sub) analyses of IMPROVE-IT.

scholarly journals A Peri-Implant Disease Risk Score for Patients with Dental Implants: Validation and the Influence of the Interval between Maintenance Appointments

2019 ◽  
Vol 8 (2) ◽  
pp. 252 ◽  
Author(s):  
Miguel de Araújo Nobre ◽  
Francisco Salvado ◽  
Paulo Nogueira ◽  
Evangelista Rocha ◽  
Peter Ilg ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Disease Risk ◽  
Disease Incidence ◽  
Risk Groups ◽  
Risk Profile ◽  
Moderate Risk ◽  
C Statistic ◽  
Disease Risk Score ◽  
Very High

Background: There is a need for tools that provide prediction of peri-implant disease. The purpose of this study was to validate a risk score for peri-implant disease and to assess the influence of the recall regimen in disease incidence based on a five-year retrospective cohort. Methods: Three hundred and fifty-three patients with 1238 implants were observed. A risk score was calculated from eight predictors and risk groups were established. Relative risk (RR) was estimated using logistic regression, and the c-statistic was calculated. The effect/impact of the recall regimen (≤ six months; > six months) on the incidence of peri-implant disease was evaluated for a subset of cases and matched controls. The RR and the proportional attributable risk (PAR) were estimated. Results: At baseline, patients fell into the following risk profiles: low-risk (n = 102, 28.9%), moderate-risk (n = 68, 19.3%), high-risk (n = 77, 21.8%), and very high-risk (n = 106, 30%). The incidence of peri-implant disease over five years was 24.1% (n = 85 patients). The RR for the risk groups was 5.52 (c-statistic = 0.858). The RR for a longer recall regimen was 1.06, corresponding to a PAR of 5.87%. Conclusions: The risk score for estimating peri-implant disease was validated and showed very good performance. Maintenance appointments of < six months or > six months did not influence the incidence of peri-implant disease when considering the matching of cases and controls by risk profile.

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