Different prognostic effect of postoperative chemoradiation therapy on diploid and nondiploid high-risk rectal cancers

1998 ◽  
Vol 41 (12) ◽  
pp. 1494-1499 ◽  
Author(s):  
Reiping Tang ◽  
Yet-Sen Ho ◽  
Hong-Hua Chen ◽  
Lai-Chu See ◽  
Jeng-Yi Wang
Keyword(s):  
High Risk ◽  
Chemoradiation Therapy ◽  
Prognostic Effect ◽  
Rectal Cancers ◽  
Postoperative Chemoradiation

Postoperative Chemoradiation Therapy in High-Risk Salivary Gland Cancers

2014 ◽  
Vol 90 (1) ◽  
pp. S182-S183
Author(s):  
J.J. Caudell ◽  
M. Mifsud ◽  
N.G. Rao ◽  
J. McCaffrey ◽  
J. Russell ◽  
...  
Keyword(s):  
Salivary Gland ◽  
High Risk ◽  
Chemoradiation Therapy ◽  
Postoperative Chemoradiation

IORT in Integrated Treatment of High-Risk Rectal Cancers

1997 ◽  
pp. 209-212 ◽  
Author(s):  
L. Sofo ◽  
C. Ratto ◽  
V. Valentini ◽  
A. Piermattei ◽  
L. Trodella ◽  
...  
Keyword(s):  
High Risk ◽  
Integrated Treatment ◽  
Rectal Cancers

Meta-analyzing the prevalence and prognostic effect of antipsychotic exposure in clinical high-risk (CHR): when things are not what they seem

2020 ◽  
pp. 1-9
Author(s):  
Andrea Raballo ◽  
Michele Poletti ◽  
Antonio Preti
Keyword(s):  
High Risk ◽  
Meta Analysis ◽  
Prognostic Impact ◽  
Clinical High Risk ◽  
Qualitative Synthesis ◽  
Prognostic Effect ◽  
Inverse Variance ◽  
Arcsine Transformation ◽  
Estimate Prevalence

Abstract Background The clinical high-risk (CHR) for psychosis paradigm is changing psychiatric practice. However, a widespread confounder, i.e. baseline exposure to antipsychotics (AP) in CHR samples, is systematically overlooked. Such exposure might mitigate the initial clinical presentation, increase the heterogeneity within CHR populations, and confound the evaluation of transition to psychosis at follow-up. This is the first meta-analysis examining the prevalence and the prognostic impact on transition to psychosis of ongoing AP treatment at baseline in CHR cohorts. Methods Major databases were searched for articles published until 20 April 2020. The variance-stabilizing Freeman-Tukey double arcsine transformation was used to estimate prevalence. The binary outcome of transition to psychosis by group was estimated with risk ratio (RR) and the inverse variance method was used for pooling. Results Fourteen studies were eligible for qualitative synthesis, including 1588 CHR individuals. Out of the pooled CHR sample, 370 individuals (i.e. 23.3%) were already exposed to AP at the time of CHR status ascription. Transition toward full-blown psychosis at follow-up intervened in 112 (29%; 95% CI 24–34%) of the AP-exposed CHR as compared to 235 (16%; 14–19%) of the AP-naïve CHR participants. AP-exposed CHR had higher RR of transition to psychosis (RR = 1.47; 95% CI 1.18–1.83; z = 3.48; p = 0.0005), without influence by age, gender ratio, overall sample size, duration of the follow-up, or quality of the studies. Conclusions Baseline AP exposure in CHR samples is substantial and is associated with a higher imminent risk of transition to psychosis. Therefore, such exposure should be regarded as a non-negligible red flag for clinical risk management.

High Risk Myeloma Is Characterized By the Bi-Allelic Inactivation of CDKN2C and RB1

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 4416-4416
Author(s):  
Shweta S. Chavan ◽  
Christoph Heuck ◽  
Jie He ◽  
Rusiana Tytarenko ◽  
Shayu Deshpande ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
High Risk ◽  
Research Funding ◽  
Prognostic Markers ◽  
Medical Sciences ◽  
Genomic Alterations ◽  
Employment Equity ◽  
Prognostic Effect ◽  
Equity Ownership ◽  
Gene Alterations

Abstract Introduction Gene expression and comprehensive genomic profiling (CGP) underscore the importance of multiple myeloma (MM) being driven by diverse genomic abnormalities and are increasingly being integrated into personalized treatment algorithms to optimize clinical outcomes, in particular that of high risk disease. Furthermore, CGP allow for ultra-deep sequencing of various clinically relevant and targetable genomic alterations using a single assay, with an advantage of detection of low frequency variants. Methods Samples from 578 patients (monoclonal gammopathy of undetermined significance, MGUS, (n=19); smoldering multiple myeloma, SMM, (n=42); or multiple myeloma, MM, (n=517; 87 newly diagnosed (NDMM), 107after treatment (TRMM), and 323 at relapse (RLMM)) were analyzed using the FoundationOne® Heme (F1H) assay. 50 ng of DNA and RNA from CD138+ selected cells were analyzed for genomic alterations including base substitutions, indels, copy number alterations, and rearrangements. Sequencing was performed to a median depth of 468x in 405 genes, as well as selected introns of 31 genes involved in rearrangements. Additionally, matched Gene Expression Profiling (GEP) was performed using Affymetrix U133 Plus 2 array, and GEP70-defined risk status and molecular subgroups were calculated. Results Results of the F1H assay revealed the most common alterations in MM to be: KRAS (28.8%), NRAS (23.2%), TP53 (17.4%), BRAF (6.8%), CDKN2C (6.0%), RB1 (5.8%), TRAF3 (5.8%), DNMT3A (3.9%), TET2 (3.7%) and ATM (2.5%), including mutations, homozygous loss and rearrangements. When these frequencies were split across GEP70 risk groups, TP53, CDKN2C/FAF1, RB1, and the t(4;14) were significantly different (p<0.05). As the disease progressed from MGUS to relapse, the number of mutations showed an increasing trend. Likewise, there were significant differences in the number of mutations between CCND1/CCND3 (CD-1) and low bone disease, CD-1 and hyperdiploid, and hyperdiploid and proliferation groups. In order to identify independent prognostic genomic alterations, we performed a multivariate Cox regression analysis on all the gene alterations that were present in at least 5% of the patient cohort, resulting in identification of four significant alterations: the t(4;14), mutation/loss of TP53, CDKN2C/FAF1 or RB1. Alterations in CDKN2C and RB1 were associated with the PR group. When the MM samples were split according to type (NDMM, TRMM, RLMM) the effect on survival of each of these alteration was more pronounced at relapse, but still present at diagnosis for CDKN2C and t(4;14). Bi-allelic events in CDKN2C, TP53 and RB1 were examined, by both homozygous deletion and monosomy with accompanying mutation, showing the rate of inactivation increased from 9.2% in NDMM to 17.9% at relapse, indicating that bi-allelic inactivation of these genes are correlated with relapse. CDKN2C and TP53 are known prognostic markers but the prognostic significance of RB1 has been debated. Previous data have shown that the association of t(4;14) with del(13q) results in insignificance of del(13q) as a prognostic marker in multivariate analyses. Here, we confirmed that the prognostic effect of RB1 is not due to association with t(4;14), and show that patients with either the t(4;14) or alteration of RB1 have a poor prognosis, which is worse when both lesions are present. Conclusions Using the F1H assay, we establish the mutational spectrum in MM, identifying lesions associated with high risk. This is the first study in MM to identify and confirm the poor prognostic effect of RB1 driven by bi-allelic inactivation, which is more prevalent at relapse. Furthermore, we determined the gene alterations that are independent prognostic markers in relapsed MM, thereby identifying novel therapeutic targets. Disclosures He: Foundation Medicine, Inc: Employment, Equity Ownership. Bailey:Foundation Medicine, Inc: Employment, Equity Ownership. Ashby:University of Arkansas for Medical Sciences: Employment. Zhong:foundation medicine: Employment. Nahas:Foundation medicine: Employment. Ali:Foundation Medicine: Employment, Equity Ownership. Vergillo:Foundation Medicine, Inc: Employment. Ross:Foundation Medicine, Inc: Employment. Miller:Foundation Medicine: Employment, Equity Ownership. Stephens:Foundation Medicine: Employment, Equity Ownership. Barlogie:Signal Genetics: Patents & Royalties. Mughal:Foundation Medicine: Employment, Equity Ownership. Davies:Celgene: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. Morgan:Takeda: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Bristol Meyers: Consultancy, Honoraria; Janssen: Research Funding; Univ of AR for Medical Sciences: Employment.

Effect of number of computed tomography (CT) scans during follow-up (FUP) of patients with clinical stage I (CSI) seminoma: A trial-level meta-analysis.

2018 ◽  
Vol 36 (6_suppl) ◽  
pp. 564-564
Author(s):  
Patrizia Giannatempo ◽  
Daniele Raggi ◽  
Elena Tagliabue ◽  
Mario Catanzaro ◽  
Davide Biasoni ◽  
...  
Keyword(s):  
High Risk ◽  
Meta Analysis ◽  
Statistical Significance ◽  
Clinical Stage ◽  
Continuous Variable ◽  
Ct Scans ◽  
Occurrence Rate ◽  
Prognostic Effect ◽  
Level Data ◽  
The Impact

564 Background: Despite the overall high cure-rate for patients (pts) with CSI seminoma (sem) regardless of the intervention used, huge discrepancy exists in the number of CT scans that are proposed to pts during FUP period, mainly during active surveillance (AS). The impact of such discrepancy in diagnosing pts with a high-risk relapse was assessed in published literature with a meta-analysis (MA). Methods: We searched for arms of studies of AS or active treatment (AT, adjuvant chemotherapy and radiotherapy) in pts with CSI sem. Meta-analytic techniques were used to pool and compare study level data of AS and AT groups and to study the impact of the number of CT scans (as a continuous variable) during FUP upon the % of pts with CSIII or with IGCCCG intermediate (int) prognosis sem at relapse. Results: 22 studies were analyzed (33 arms, n = 11025 pts). 39.6% had a high-risk sem, 38.8% (n = 4274) underwent AS vs 61.2% (n = 6751) AT. The number of CT scans ≤2y ranged 4-8, and 0-7 for AS and AT groups. Overall, 922 pts experienced a relapse (651 in AS and 271 in AT arms), 73.9% <2y and 22.3% at 2-5y FUP. Statistical modeling showed that the estimated rates of CSIII relapse (6% in AS, 32% in AT group, p = 0.0068) and int prognosis relapse (2% in AS, 11% in AT group, p = 0.0051), were divergent for the two groups. A higher number of CT scans in the first 2 years of FUP tended to reduce the occurrence rate of both endpoints, but failed to reach statistical significance in AS (p = 0.334 for CSIII, unidentifiable for int prognosis relapse), as well as in AT (p = 0.438, p = 0.103). The number of CT scans in 3-5y FUP had an even weaker prognostic effect. Similar trends were observed in AS cohort after adjusting for the CSI risk group. Conclusions: In this trial-level MA we did not find a statistically-significant association between the number of CT scans performed during FUP of CSI sem pts and the diagnosis of high-risk relapses. Huge discrepancy in the total number of CT scans was generally found between arms. In contrast, as expected, the pattern of relapse of CSI sem was different according to the treatment group. Based on these results, there is room for consistently reducing the number of CT scans during FUP of CSI sem pts undergoing AS.

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