External validation of the Glasgow prognostic score (mGPS) for renal cancer.

378 Background: Inflammation has been termed the 7th hallmark of cancer (Hanahan and Weinberg Cell 2011). Measurement of systemic inflammatory responses in malignancy is possible using a selective combination of two commonly available, cost-effective serum assays. The combination of these two serum markers, C-reactive protein (CRP) and albumin, is termed the modified Glasgow prognostic score (mGPS), and is strongly correlated with outcome in a variety of cancers, including mRCC. Recently, mGPS has been shown to be predictive of outcome in localized RCC (ASCO GU 2010 #390). We sought to externally validate these results. Methods: Nephrectomized patients with clinically localized (T1-T4N0M0) clear cell RCC with negative surgical margins were followed for a mean of 25 months (range: 1-81 months). Relapse and survival was identified through routine follow-up. Patients were categorized by mGPS score as Low Risk (mGPS = 0 points), Intermediate Risk (mGPS = 1 point), and High Risk (mGPS = 2 points). One point was assigned to patients for an elevated CRP (>10 mg/L) and hypoalbuminemia (<3.5 mg/dL). Patients with normal CRP and hypoalbuminemia were assigned 0 points. Kaplan-Meier and multivariate Cox regression analyses examined relapse-free survival (RFS) and overall survival (OS) across patient and disease characteristics. Results: Of 248 patients, 17.9% relapsed and 18.6% died. Of Low, Intermediate, and High Risk patients, 7.2%, 7.7%, and 45.5%, respectively relapsed and 5.2%, 15.4%, and 39.4%, respectively died during the study. In multivariate analysis including stage and grade, mGPS was significantly associated with RFS and OS. Compared to Low-Risk patients, High-Risk patients experienced a 3-fold (OR: 2.906, 95% CI: 1.055-8.001) increased risk of relapse and 4-fold (HR: 3.722, 95% CI: 1.046-13.245) increased risk of mortality. AUC is 0.813, which compares very favorably to existing prognostic algorithms. Conclusions: In this external validation cohort of US patients, mGPS continues to be a predictor of relapse and overall mortality following nephrectomy for localized RCC. Clinicians may consider using mGPS as an adjunct to identify high-risk patients for possible enrollment into clinical trials, or for patient counseling.

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The Risk of Stroke Using CHA2 DS2 -VASc Score in Hemodialysis Patients at a Tertiary Hospital in Riyadh, Saudi Arabia

Journal of Clinical Review & Case Reports ◽

10.33140/jcrc.04.07.01 ◽

2019 ◽

Vol 4 (7) ◽

Keyword(s):

Risk Factors ◽

High Risk ◽

Stroke Risk ◽

Hemodialysis Patients ◽

Low Risk ◽

High Risk Patients ◽

Stroke Risk Factors ◽

Increased Risk ◽

Risk Patients ◽

History Of

Introduction: Patients undergoing hemodialysis are at increased risk of stroke. However, less known about the impact of some of the stroke risk factors, and the value of stroke risk scores in determining the risk in those patients. Our main goal. To assess the risk factors for stroke in hemodialysis patients and the use of the new CHA2DS2-VASc score for stroke assessment. Methods: Single center, retrospective cohort study of 336 patients undergoing hemodialysis from June 24, 2018, to September 6, 2018, was recruited. Baseline demographics, clinical, and laboratory data were collected. We calculated the CHA2 DS2 -VASc score for stroke assessment in all patients and categorized them into high, moderate and low risk patients according to CHA2 DS2 - VASc score and subcategorized them to two groups atrial fibrillation (AFib) and Non- Atrial fibrillation (Non AFib) patients. Results: 336 patients were included in our study; the majority of patients were at high risk with a CHA2 DS2 -VASc Score mean of 2.9± 1.5, although history of stroke was observed only in 15 patients (4.46%). According to CHA2 DS2 - VASc score, 280 patients were at high risk, 172 (51.19%) were high-risk patients on treatment (anticoagulant or antiplatelet) and 108(32.14%) patients were high risk patients not on treatment 48 were at moderate risk (14.28%) and 8 were at low risk (2.38 %). Patients were divided into subgroups as non-AFib and AFib. In non-AFib patients 320 (95.23%), high-risk patients 103 (32.18%) were not treated; high-risk patients with treatment are 162 (50.62%), moderate patients were 47 (14.68%), 8(2.5%) was in low risk. AFib patients were 16 with a mean CHA2 DS2 -VASc score of 4.4±1.1. Patients with AFib were all at high risk except 1 was at moderate risk (6.25%). There were 11 (68.75%) patients on treatment and 5 (31.25%) patients not on treatment. The risk factors for stroke that were statistically significant in increasing score risk for all patients were: age > 65 (95% CI, -2.04– -1.29; p = 0.000), being female (95% CI, -1.36– -0.68; p = 0.000) hypertension (95% CI, -2.59– -1.37; p = 0.000), diabetes (95% CI, -2.10– -1.50; p = 0.000), CVD (95% CI, -2.07– -1.24; p=0.000), history of stroke or TIA (95% CI, -3.70– -2.03; p = 0.000), CHF or LVEF (95% CI, -2.28– - 0.91; p = 0.000). Conclusions: The risk of stroke in hemodialysis patients is significant according to the use of CHA2 DS2 -VASc score in Non-AFib hemodialysis patients shows supportive evidence of increased risk of stroke in those patients, which suggest the importance of close monitoring of patients with stroke risk factors by the nephrologist and the stroke team which will lead to the initiation of early prophylaxis in those patients.

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A tool to identify patients with embolic stroke of undetermined source at high recurrence risk

Neurology ◽

10.1212/wnl.0000000000008571 ◽

2019 ◽

Vol 93 (23) ◽

pp. e2094-e2104 ◽

Cited By ~ 1

Author(s):

George Ntaios ◽

Georgios Georgiopoulos ◽

Kalliopi Perlepe ◽

Gaia Sirimarco ◽

Davide Strambo ◽

...

Keyword(s):

High Risk ◽

Cox Regression ◽

External Validation ◽

Low Risk ◽

Embolic Stroke ◽

Stroke Recurrence ◽

Intermediate Risk ◽

Cox Regression Analysis ◽

Derivation Cohort ◽

Risk Patients

ObjectiveA tool to stratify the risk of stroke recurrence in patients with embolic stroke of undetermined source (ESUS) could be useful in research and clinical practice. We aimed to determine whether a score can be developed and externally validated for the identification of patients with ESUS at high risk for stroke recurrence.MethodsWe pooled the data of all consecutive patients with ESUS from 11 prospective stroke registries. We performed multivariable Cox regression analysis to identify predictors of stroke recurrence. Based on the coefficient of each covariate of the fitted multivariable model, we generated an integer-based point scoring system. We validated the score externally assessing its discrimination and calibration.ResultsIn 3 registries (884 patients) that were used as the derivation cohort, age, leukoaraiosis, and multiterritorial infarct were identified as independent predictors of stroke recurrence and were included in the final score, which assigns 1 point per every decade after 35 years of age, 2 points for leukoaraiosis, and 3 points for multiterritorial infarcts (acute or old nonlacunar). The rate of stroke recurrence was 2.1 per 100 patient-years (95% confidence interval [CI] 1.44–3.06) in patients with a score of 0–4 (low risk), 3.74 (95% CI 2.77–5.04) in patients with a score of 5–6 (intermediate risk), and 8.23 (95% CI 5.99–11.3) in patients with a score of 7–12 (high risk). Compared to low-risk patients, the risk of stroke recurrence was significantly higher in intermediate-risk (hazard ratio [HR] 1.78, 95% CI 1.1–2.88) and high-risk patients (HR 4.67, 95% CI 2.83–7.7). The score was well-calibrated in both derivation and external validation cohorts (8 registries, 820 patients) (Hosmer-Lemeshow test χ2: 12.1 [p = 0.357] and χ2: 21.7 [p = 0.753], respectively). The area under the curve of the score was 0.63 (95% CI 0.58–0.68) and 0.60 (95% CI 0.54–0.66), respectively.ConclusionsThe proposed score can assist in the identification of patients with ESUS at high risk for stroke recurrence.

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Multi-Omics Profiling Identifies Risk Hypoxia-Related Signatures for Ovarian Cancer Prognosis

Frontiers in Immunology ◽

10.3389/fimmu.2021.645839 ◽

2021 ◽

Vol 12 ◽

Author(s):

Xingyu Chen ◽

Hua Lan ◽

Dong He ◽

Runshi Xu ◽

Yao Zhang ◽

...

Keyword(s):

Ovarian Cancer ◽

High Risk ◽

Poor Prognosis ◽

Cox Regression ◽

Risk Group ◽

High Risk Group ◽

Low Risk ◽

Cancer Prognosis ◽

High Risk Patients ◽

Risk Patients

BackgroundOvarian cancer (OC) has the highest mortality rate among gynecologic malignancy. Hypoxia is a driver of the malignant progression in OC, which results in poor prognosis. We herein aimed to develop a validated model that was based on the hypoxia genes to systematically evaluate its prognosis in tumor immune microenvironment (TIM).ResultsWe identified 395 hypoxia-immune genes using weighted gene co-expression network analysis (WGCNA). We then established a nine hypoxia-related genes risk model using least absolute shrinkage and selection operator (LASSO) Cox regression, which efficiently distinguished high-risk patients from low-risk ones. We found that high-risk patients were significantly related to poor prognosis. The high-risk group showed unique immunosuppressive microenvironment, lower antigen presentation, and higher levels of inhibitory cytokines. There were also significant differences in somatic copy number alterations (SCNAs) and mutations between the high- and low-risk groups, indicating immune escape in the high-risk group. Tumor immune dysfunction and exclusion (TIDE) and SubMap algorithms showed that low-risk patients are significantly responsive to programmed cell death protein-1 (PD-1) inhibitors.ConclusionsIn this study, we highlighted the clinical significance of hypoxia in OC and established a hypoxia-related model for predicting prognosis and providing potential immunotherapy strategies.

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Validation of the High-Risk Prognostic Score Defined By the Presence of Mutations in NRAS or TP53 in a Cohort of 497 Patients with Acute Myeloid Leukemia

Blood ◽

10.1182/blood-2020-137467 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 4-5

Author(s):

Rosa Ayala ◽

Pau Montesinos ◽

Eva Barragán ◽

Joaquin Martinez-Lopez ◽

Miguel A. Sanz ◽

...

Keyword(s):

High Risk ◽

Research Funding ◽

Low Dose ◽

Prognostic Score ◽

Low Risk ◽

Hypomethylating Agents ◽

Younger Patients ◽

High Risk Patients ◽

Risk Patients ◽

Low Dose Cytarabine

INTRODUCTION Older AML patients have a different mutational landscape compared to younger patients. The prognostic classification of AML proposed by the European Leukemia Net (2017) is based on the presence of mutations in FLT3 (ITD), NPM1, CEBPA, RUNX1, ASXL1 and TP53. However, our group has identified a high-risk prognostic score in older patients with AML, who are undergoing treatment with azacitidine or low-dose cytarabine plus fludarabine, which predict a shorter survival. OBJECTIVE Validation of the previously identified high-risk prognostic score, defined by the presence of mutations in NRAS or TP53, in 3 cohorts of patients with AML who have been studied by NGS with a custom panel in the healthcare practice (Cohort 1: Intensive treatment; cohort 2: Hypomethylating agents and cohort 3: low-dose cytarabine) METHODS The study was conducted on a series of 535 patients diagnosed with AML (mean age 67). Patients evaluated for OS and RFS were 497 cases: intensive treatment (schemes 3+7 or similar; n=238), hypomethylating agents (azacitidine, decitabine; n=113) and treated with low-dose cytarabine (n=146). 38 patients on supportive therapy were excluded. Mutational profile was identified at diagnosis by NGS technique (Ion Torrent System), using a custom panel of 41 genes involved in myeloid pathologies: ASXL1, BCOR, BCORL1, CALR, CBL, CEBPA, DNMT3A, EPAS1, EPOR, ETV6, EZH2, FLT3, IDH1, IDH2, JAK2, KDM6A, KIT, KMT2A, KRAS, MPL, NF1, NPM1, NRAS, PHF6, PRPF40B, RAD21, RUNX1, SETBP1, SF3A1, SF3B1, SH2B3, SMC1A, SRSF2, STAG2, TET2, THPO, TP53, U2AF1, VHL, WT1 y ZRSR2. The mean OS and RFS were compared by means of Kaplan-Meier curves using the log-rank test. The bioinformatics analysis was performed with the SPSS software. RESULTS The median SG and RFS of this series was 10.8 months and 6.9 months respectively. The mutational profile in older patients was different from that analyzed in younger patients. We observed greater presence of mutations in NPM1 in younger patients (34.4 vs 18.6%, p=0.04), while in older than 65 years were identified more mutations in ASXL1 (3.9 vs 16.6%, p<0.01) or RUNX1 (8.6 vs 18.4%, p=0.005). No differences were observed in TP53, NRAS, TET2, DNMT3A and FLT3-ITD. However, we detected differences in VAF distribution of variants with lower VAF in younger patients in NPM1 (0.9 vs 5%, p=0.001), RUNX1 (4.1 vs 9.1%, p=0.003), ASXL1 (1.5 vs 8.2%, p<0.001) and TP53 (5.9 vs 14%, p<0.001) The median OS for intensively treated patients with a low-risk prognostic score was 49.1 months (17.56, 80.60) vs. 18.9 (14.98, 22.79) for high-risk patients (p=0.015). The median RFS was 45.2 months (5.2; 85.14) for low-risk patients vs. 42.1 (18.35; 65.92) for high-risk patients (p=0.167). The median OS for low-risk patients treated with hypomethylating agents was 13.2 months (9.02, 17.47) vs. 4.8 (1.6, 7.9) for patients with a high-risk score (p=0.002). The median RFS was 9.9 months (7.4, 12.3) for low-risk patients vs. 14.9 (10.1, 19.8) for high-risk patients (p=0.682). The median OS for patients treated with low-dose cytarabine was 8.4 months (4.9, 12.1) for low risk vs. 3.1 (1.22, 4.94) for high risk (p<0.001). The median RFS was 6.8 months (5.28, 8.42) for low-risk patients vs. 3.7 (2.75, 4.66) for those with a high-risk score (p=0.008). CONCLUSIONS We have confirm that exist differences in the mutational profile between older and younger AML patients and these differences have implications in the definition of risk of these patients. The prognostic score defined by the presence of mutations in the TP53 and NRAS genes, has been validated as an adverse prognostic factor across the three treatment groups studied (intensive treatment, hypomethylating agents and low-dose cytarabine) for OS, and this score no predict risk of relapse in the cohorts with intensive and hypomethylating treatments at difference to the low-dose cytarabine cohort. ML.M. enjoys a research grant from the Spanish Society of Hematology and Hemotherapy. This work has been financed thanks to the aid PI16/01225 and PI19/01518, from the Instituto de Salud Carlos III (Ministerio de Economía, Industria y Competitividad) and co-financed by the European Development Fund. Disclosures Montesinos: Astellas, Novartis, Janssen: Speakers Bureau; Celgene, Pfizer, Abbvie: Consultancy; Pfizer, Abbvie, Daiichi Sankyo: Research Funding. Martinez-Lopez:Incyte: Consultancy, Research Funding; Janssen: Consultancy, Honoraria; Janssen-cilag: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy; BMS: Consultancy, Research Funding. Sanz:Teva, Daiichi-Sankyo, Orsenix, AbbVie, Novartis, and Pfizer: Other: Consulting or Advisory Role.

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P4: EXTERNAL VALIDATION OF THE OUTCOMES AFTER KIDNEY INJURY IN SURGERY (OAKS) PROGNOSTIC SCORE TO PREDICT POSTOPERATIVE ACUTE KIDNEY INJURY IN PATIENTS UNDERGOING MAJOR ELECTIVE COLORECTAL SURGERY

British Journal of Surgery ◽

10.1093/bjs/znab117.089 ◽

2021 ◽

Vol 108 (Supplement_1) ◽

Author(s):

Keyword(s):

Acute Kidney Injury ◽

High Risk ◽

Angiotensin Receptor Blockers ◽

Prognostic Score ◽

External Validation ◽

Kidney Injury ◽

Elective Colorectal Surgery ◽

High Risk Patients ◽

Risk Patients ◽

Postoperative Aki

Abstract Background Postoperative Acute Kidney Injury (AKI) is associated with significant morbidity and mortality following major gastrointestinal surgery. The Outcomes After Kidney injury in Surgery (OAKS) prognostic score risk stratifies patients undergoing major gastrointestinal surgeries for 7-day postoperative acute kidney injury (AKI). This study aimed to perform external validation of an international elective colorectal cohort. Method The Ileus MAnagement INternational (IMAGINE) audit (January to April 2018) included consecutive adults undergoing elective colorectal resection or stoma reversal across Europe and Australasia. Multivariate logistic regression was performed using data on 7-day AKI and the OAKS prognostic variables (age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery, and preoperative use of angiotensin-converting enzyme inhibitors or angiotensin receptor blockers). Discrimination and calibration (Hosmer–Lemeshow test) were assessed on prediction of patients at high-risk (>20%) of postoperative AKI. Result Of 4046 patients included across 338 centres, 13.4% (n=542) developed 7-day AKI. The model discrimination was 0.67 (95% CI = 0.65-0.70), identifying high-risk patients with low sensitivity (0.28, 95% CI: 0.25-0.32) but high specificity (0.90, 95% CI = 0.89-0.91). Furthermore, the model demonstrated good calibration (p=0.518). Conclusion Discrimination of the OAKS score for patients at high-risk of postoperative AKI in this cohort is good, and remains consistent with the derivation cohort. High-risk patients identified may represent a feasible target for interventions aimed at mitigating AKI. Take-home message Prognostic risk scores may be helpful in predicting risk of postoperative acute kidney injury in patients undergoing major abdominal surgery.

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Colorectal cancer risk following polypectomy in a multicentre, retrospective, cohort study: an evaluation of the 2020 UK post-polypectomy surveillance guidelines

Gut ◽

10.1136/gutjnl-2020-323411 ◽

2021 ◽

pp. gutjnl-2020-323411

Author(s):

Amanda J Cross ◽

Emma C Robbins ◽

Kevin Pack ◽

Iain Stenson ◽

Bhavita Patel ◽

...

Keyword(s):

Colorectal Cancer ◽

High Risk ◽

General Population ◽

Cox Regression ◽

Population Based ◽

Low Risk ◽

High Grade Dysplasia ◽

High Grade ◽

High Risk Patients ◽

Risk Patients

ObjectiveColonoscopy surveillance aims to reduce colorectal cancer (CRC) incidence after polypectomy. The 2020 UK guidelines recommend surveillance at 3 years for ‘high-risk’ patients with ≥2 premalignant polyps (PMPs), of which ≥1 is ‘advanced’ (serrated polyp (or adenoma) ≥10 mm or with (high-grade) dysplasia); ≥5 PMPs; or ≥1 non-pedunculated polyp ≥20 mm; ‘low-risk’ patients without these findings are instead encouraged to participate in population-based CRC screening. We examined the appropriateness of these risk classification criteria and recommendations.DesignRetrospective analysis of patients who underwent colonoscopy and polypectomy mostly between 2000 and 2010 at 17 UK hospitals, followed-up through 2017. We examined CRC incidence by baseline characteristics, risk group and number of surveillance visits using Cox regression, and compared incidence with that in the general population using standardised incidence ratios (SIRs).ResultsAmong 21 318 patients, 368 CRCs occurred during follow-up (median: 10.1 years). Baseline CRC risk factors included age ≥55 years, ≥2 PMPs, adenomas with tubulovillous/villous/unknown histology or high-grade dysplasia, proximal polyps and a baseline visit spanning 2–90 days. Compared with the general population, CRC incidence without surveillance was higher among those with adenomas with high-grade dysplasia (SIR 1.74, 95% CI 1.21 to 2.42) or ≥2 PMPs, of which ≥1 was advanced (1.39, 1.09 to 1.75). For low-risk (71%) and high-risk (29%) patients, SIRs without surveillance were 0.75 (95% CI 0.63 to 0.88) and 1.30 (1.03 to 1.62), respectively; for high-risk patients after first surveillance, the SIR was 1.22 (0.91 to 1.60).ConclusionThese guidelines accurately classify post-polypectomy patients into those at high risk, for whom one surveillance colonoscopy appears appropriate, and those at low risk who can be managed by non-invasive screening.

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Transitional B cell cytokines predict renal allograft outcomes

Science Translational Medicine ◽

10.1126/scitranslmed.abe4929 ◽

2021 ◽

Vol 13 (582) ◽

pp. eabe4929

Author(s):

Aravind Cherukuri ◽

Alan D. Salama ◽

Rajil Mehta ◽

Kanishka Mohib ◽

Leting Zheng ◽

...

Keyword(s):

B Cells ◽

High Risk ◽

Renal Allograft ◽

External Validation ◽

Predictive Biomarker ◽

Low Risk ◽

First Year ◽

Time Averaging ◽

High Risk Patients ◽

Risk Patients

Early immunological biomarkers that predict rejection and chronic allograft loss are needed to inform preemptive therapy and improve long-term outcomes. Here, we prospectively examined the ratio of interleukin-10 (IL-10) to tumor necrosis factor–α (TNFα) produced by transitional-1 B cells (T1B) 3 months after transplantation as a predictive biomarker for clinical and subclinical renal allograft rejection and subsequent clinical course. In both Training (n = 162) and Internal Validation (n = 82) Sets, the T1B IL-10/TNFα ratio 3 months after transplantation predicted both clinical and subclinical rejection anytime in the first year. The biomarker also predicted subsequent late rejection with a lead time averaging 8 months. Among biomarker high-risk patients, 60% had early rejection, of which 48% recurred later in the first posttransplant year. Among high-risk patients without early rejection, 74% developed rejection later in the first year. In contrast, only 5% of low-risk patients had early and 5% late rejection. The biomarker also predicted rejection in an External Validation Set (n = 95) and in key patient subgroups, confirming generalizability. Biomarker high-risk patients exhibited progressively worse renal function and decreased 5-year graft survival compared to low-risk patients. Treatment of B cells with anti-TNFα in vitro augmented the IL-10/TNFα ratio, restored regulatory activity, and inhibited plasmablast differentiation. To conclude, the T1B IL-10/TNFα ratio was validated as a strong predictive biomarker of renal allograft outcomes and provides a rationale for preemptive therapeutic intervention with TNF blockade.

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