scholarly journals CLL: A Prognostic Model Comprising Only Two Biomarkers (IGHV Mutational Status and FISH-Cytogenetics) Separates Patients with Different Prognosis and Simplifies the CLL-IPI.

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 3205-3205 ◽  
Author(s):  
Julio Delgado ◽  
Michael Doubek ◽  
Tycho Baumann ◽  
Jana Kotaskova ◽  
Pablo Mozas ◽  
...  
Keyword(s):  
High Risk ◽  
Expert Testimony ◽  
Prognostic Model ◽  
Prognostic Index ◽  
Continuous Variables ◽  
Fish Cytogenetics ◽  
C Statistic ◽  
Mutational Status ◽  
Clinical Stages ◽  
Very High

Abstract Background: Survival of pts with chronic lymphocytic leukemia (CLL) ranges from a few years to a normal lifespan. Clinical stages (i.e. Rai, Binet) are the basis for CLL prognostication but do not reflect the complex biology of CLL, which ultimately shapes the disease heterogeneity. Recently, a CLL-International Prognostic Index (CLL-IPI) which includes five clinical and biological variables (i.e. age, IGHV mutational status, del(17p), beta2-microglobulin [B2M] and Rai or Binet stages) and stratifies pts into four different categories has been proposed. This prognostic index is obtained by the sum of the score given to each parameter and includes dichotomized continuous variables. The aim of this study was to determine whether a prognostic model based only on biomarkers could separate CLL patients with different outcomes and simplify the CLL-IPI. Material and Methods: Five hundred twenty-four CLL pts from the Hospital Clínic, Barcelona, in whom information at diagnosis included age, clinical stage (Rai and Binet), IGHV mutational status, B2M, and FISH-cytogenetics were analyzed. For validation purposes a cohort of 417 pts from the Brno Hospital, Czech Republic was used. The two series included patients as seen in clinical practice. Primary endpoints were overall survival (OS) and time to first treatment (TTFT). The internal validity of the models was evaluated using bootstrapping, and the discriminatory value by c-statistics. Double sided P values < .05 were considered significant. Results: First, we confirmed that all five covariates included in the CLL-IPI were independently predictive of OS. Both sets of five covariates (age + B2M + IGHV + FISH + Rai or Binet) were incorporated into the regression models. All four patient subgroups had a significantly different survival (c-statistic: 0.72), although the high- and very-high risk groups overlapped and the number of patients in the very-high-risk group was small. We then evaluated all possible combinations of these five covariates to identify the simplest model with robust discriminatory value. A prognostic model based on IGHV mutational status + FISH [del(17p) and/or del(11q)] separated three subgroups of pts [i.e, good-biomarkers (mutated IGHV + no poor FISH cytogenetics), intermediate-biomarkers (either unmutated IGHV or poor FISH cytogenetics), and poor biomarkers (unmutated IGHV + poor FISH cytogenetics)] with different prognosis (c-statistic: 0.68). In the Barcelona series, the good-biomarkers category identified around 50% of pts from the whole series whose survival did not differ from the general population; patients with intermediate-biomarkers had a projected 10-year survival of 68%. Finally, the poor-biomarkers category captured pts with a projected 10-year survival of 17%. The corresponding TTFTs at 3 years from diagnosis were 16%, 50% and 63%, respectively (Figure). Furthermore, it separated patients with different outcome within clinical stages, notably Binet A or Rai 0, and across all age groups. This model was fully validated in the Brno series. Conclusions: The biomarkers-only CLL prognostic model presented here is based on the two most important CLL biomarkers (i.e. IGHV mutational status and FISH cytogenetics) which are included as a backbone in the CLL-IPI and other CLL prognostic systems. This model is simple, easy to apply and to remember; it separates three groups of pts rather than four; it does not contain continuous variables; it can be applied to younger and older pts, and has clinical implications. This prognostic model could be useful in CLL prognostication either alone or in combination with clinical stages and warrants prospective validation, including in patients receiving targeted therapies. Figure Figure. Disclosures Montserrat: Pharmacyclics: Consultancy; Vivia Biotech: Equity Ownership; Janssen: Honoraria, Other: travel, accommodations, expenses; Gilead: Consultancy, Other: Expert Testimony; Morphosys: Other: Expert Testimony.

A comprehensive prognostic index for patients with CLL.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 7015-7015
Author(s):  
Natali Pflug ◽  
Jasmin Bahlo ◽  
Tait D. Shanafelt ◽  
Barbara Eichhorst ◽  
Manuela Bergmann ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Mayo Clinic ◽  
External Validation ◽  
Prognostic Index ◽  
Observation Time ◽  
Clinical Staging ◽  
Newly Diagnosed ◽  
C Statistic ◽  
Very High

7015 Background: Besides clinical staging, a number of biomarkers predicting OS in CLL have been identified. The multiplicity of markers, limited information on their independent value, and a lack of understanding of how to interpret discordant markers are major barriers to use in routine clinical practice. We developed an integrated prognostic index using the database of the German CLL Study Group (GCLLSG), which was subsequently validated in a cohort of untreated CLL patients (pts) from the Mayo Clinic. Methods: The analysis was based on a dataset collected between 1997 and 2006 in 3 GCLLSG phase III trials. The external validation was performed on a series of newly diagnosed CLL pts managed at Mayo Clinic. Results: The GCLLSG dataset (1,948 physically fit pts at early and advanced stage; median age: 60 yr (range 30-81); median observation time 63.4 mo) was used as a training dataset. 7 parameters were identified as independent predictors for OS: sex, age, ECOG status, del 17p, del 11q, IGHV mutation status, thymidine kinase and β2-microglobulin. By using a weighted grading a prognostic index was derived separating four different pts groups: low risk (score 0 - 2), intermediate risk (score 3-5), high risk (score 6-10) and very high risk (score 11-14) with significant different OS rates (95.2%, 86.9%, 67.7% and 18.7% OS after 5 yr for the low, intermediate, high and very high risk group respectively (p<0.001). This prognostic index was validated in a cohort of 676 newly diagnosed, untreated pts from the Mayo Clinic (median age 61.5 yr (range 32 - 89); median observation time 47.0 mo). The 4 risk groups were reproduced with 98.3%, 95.4%, 75.4% and 10.8% OS after 5 yr. The prognostic index predicts OS independent of Rai/Binet stage and provides accurate estimations regarding time to first treatment (TTF). C-statistic is 0.75. Conclusions: Using a multi-step process including external validation, we developed a comprehensive prognostic index combining clinical, serum, and molecular information into a single risk score for pts with untreated CLL. The prognostic index provides more accurate prediction of both TTF and OS. To our knowledge it is the first prognostic model in CLL to reach the C-statistic threshold (c > 0.70) necessary to have utility at the level of the individual.

scholarly journals The CLL-international prognostic index (CLL-IPI) predicts outcomes in monoclonal B-cell lymphocytosis and Rai 0 CLL

Blood ◽  
2021 ◽  
Author(s):  
Sameer A Parikh ◽  
Kari G. Rabe ◽  
Neil E. Kay ◽  
Timothy G. Call ◽  
Wei Ding ◽  
...  
Keyword(s):  
High Risk ◽  
B Cell ◽  
Cell Count ◽  
International Prognostic Index ◽  
Multivariable Analysis ◽  
Prognostic Index ◽  
Lymphocytic Leukemia ◽  
Entire Cohort ◽  
C Statistic ◽  
Very High

The utility of the chronic lymphocytic leukemia - international prognostic index (CLL-IPI) in predicting outcomes of individuals with Rai 0 stage CLL and monoclonal B-cell lymphocytosis (MBL) is unclear. We identified 969 individuals (415 MBL and 554 Rai 0 CLL; median age=64 years, 65% men) seen at Mayo Clinic between 1/1/2001 and 10/1/2018, and ascertained time to first therapy (TTFT) and overall survival (OS). After a median follow up of 7 years, the risk of disease progression needing therapy was 2.9%/year for MBL (median=not reached) and 5%/year for Rai 0 CLL (median=10.4 years). Among patients with low, intermediate and high/very high risk CLL-IPI risk groups, the estimated 5-year risk of TTFT was 13.5%, 30%, and 58%, respectively, p&lt;0.0001 (c-statistic=0.69); and the estimated 5-year OS was 96.3%, 91.5%, and 76%, respectively, p&lt;0.0001 (c-statistic:0.65). In a multivariable analysis of absolute B-cell count with individual factors of the CLL-IPI, the absolute B-cell count was associated with shorter TTFT (hazard ratio [HR] for each 10 x 109/L increase: 1.31; p&lt;0.0001), and shorter OS (HR: 1.1; p=0.02). The OS of the entire cohort was similar to age- and sex-matched general population of Minnesota (p=0.17), although Rai 0 CLL patients with high and very high risk CLL-IPI score had significantly shorter OS (p=0.01, and p=0.0001, respectively). The results of this study demonstrate the ability of CLL-IPI to predict time from diagnosis to first treatment (an endpoint not impacted by therapy) in a large cohort of patients whose only manifestation of disease is a circulating clonal lymphocyte population.

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.

The Combination of ISS 3, High LDH and t(4;14) and/or Del(17p) Identify a Simple Prognostic Index for Overall Survival in Patients Treated with Novel Agents-Based Induction Therapy and Front-Line Autologous Stem Cell Transplantation, and Allow the Definition of a Subgroup of Patients At High-Risk of Early Death From Progressive Disease

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 598-598 ◽  
Author(s):  
Philippe Moreau ◽  
Lucie Planche ◽  
Michel Attal ◽  
Cyrille Hulin ◽  
Thierry Facon ◽  
...  
Keyword(s):  
High Risk ◽  
Board Of Directors ◽  
Progressive Disease ◽  
Prognostic Index ◽  
Early Death ◽  
Novel Agents ◽  
Advisory Committees ◽  
High Risk Disease ◽  
Definition Of ◽  
Very High

Abstract Abstract 598 Background: Several biological parameters have been described, which define patients with multiple myeloma with a high-risk of progression. Nevertheless, apart from the International Staging System (ISS), no clear, simple and reliable prognostic index has yet been identified, especially for the classification of patients with very high-risk disease. We aimed to characterize the group of patients who have a high risk of early death from progression in the context of frontline therapy using novel agents-based induction therapy and autologous stem cell transplantation. Methods: We investigated prognostic parameters of patients enrolled in the IFM2005-01 trial, which compared bortezomib-dexamethasone versus VAD induction followed by ASCT (Harousseau et al, J Clin Oncol 2010;28:4621–4629). Results: In a multivariate logistic regression analysis, the risk of death from progressive disease (and not toxicity) (42 cases out of 482 patients) within the first 2 years from the start of therapy was related to 3 independent adverse baseline characteristics: high LDH > normal value (p = 0.0014), ISS 3 (p = 0.0097) and cytogenetic abnormalities defined by the presence of either t(4;14) or 17p deletion (p = 0.0002). These 3 variables enabled the definition of a simple scoring system consisting of 4 categories (scores 0–3) that predicts for overall survival (OS). Score 0 was defined by the absence of adverse factors (neither high LDH, nor ISS 3, nor t(4;14) and/or del(17p)); in this group of patients, representing 57% of the overall population, the 4-year OS rate was 84%. A score of 1 was defined by the presence of only 1 adverse factor (either high LDH or ISS 3 or t(4;14) and/or del(17p)). The 4-year OS rate in this group of patients (32% of the overall population) was 73%. A score of 2 defined by the presence of high LDH plus ISS 3 in the absence of t(4;14) and/or del(17p), was found in 6% of the overall population. The 4-year OS rate in this group was 68%. Score 3 was defined by the presence of t(4;14) and/or del(17p) in addition to either ISS 3 or high LDH. In this group of patients, representing 5% of the overall population, the median OS was only 19 months (Figure). Conclusion: We have defined a new and simple scoring system that allows the identification of a small group of patients with very high-risk disease and a shortened survival despite the use of intensive novel agents-based therapy. These preliminary findings require confirmation using data from a large number of patients enrolled in the most recent prospective clinical trials investigating triplet induction regimens prior to ASCT. The subgroup of patients with a score of 3, which is associated with a detrimental outcome, might benefit from innovative therapeutic approaches. Disclosures: Moreau: janssen: Membership on an entity's Board of Directors or advisory committees; millenium: Membership on an entity's Board of Directors or advisory committees; celgene: Membership on an entity's Board of Directors or advisory committees. Attal:janssen: Membership on an entity's Board of Directors or advisory committees; celgene: Membership on an entity's Board of Directors or advisory committees. Hulin:janssen: Membership on an entity's Board of Directors or advisory committees; celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Facon:millenium: Membership on an entity's Board of Directors or advisory committees; janssen: Membership on an entity's Board of Directors or advisory committees; celgene: Membership on an entity's Board of Directors or advisory committees; onyx: Membership on an entity's Board of Directors or advisory committees. Kolb:celgene: Honoraria; janssen: Honoraria. Roussel:janssen: Honoraria; celgene: Honoraria. Leleu:celgene: Honoraria; janssen: Honoraria. Avet-Loiseau:janssen: Membership on an entity's Board of Directors or advisory committees; celgene: Membership on an entity's Board of Directors or advisory committees.

Cause of death in patients with newly diagnosed chronic lymphocytic leukemia (CLL) stratified by the CLL-International Prognostic Index (CLL-IPI).

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 8026-8026
Author(s):  
Yucai Wang ◽  
Sara J Achenbach ◽  
Kari G. Rabe ◽  
Tait D. Shanafelt ◽  
Timothy Call ◽  
...  
Keyword(s):  
High Risk ◽  
Cause Of Death ◽  
Risk Group ◽  
International Prognostic Index ◽  
Prognostic Index ◽  
Lymphocytic Leukemia ◽  
Intermediate Risk ◽  
Newly Diagnosed ◽  
Second Malignancies ◽  
Very High

8026 Background: CLL progression and CLL-related complications (infections and second malignancies) were the leading cause of death (COD) in a prospective cohort of CLL patients (Strati, BJH 2017). The CLL-IPI integrates major clinical and molecular prognostic factors and stratifies patients into 4 risk groups with distinct prognosis. It is unknown if COD differs according to CLL-IPI risk group in patients with newly diagnosed CLL. Methods: Patients diagnosed with CLL between 1/2000-12/2019 and seen within 1 year of diagnosis were identified from the Mayo Clinic CLL database. Cumulative incidences of cause-specific death were analyzed using Gray’s test, with deaths from different causes treated as competing events and deaths from unknown causes excluded. Results: 1276 patients were included in this study. The median age at diagnosis was 63 years (range 24-92), and 880 (69%) were male. Based on CLL-IPI score, 449 (35%) had low risk disease, 443 (35%) had intermediate risk disease, and 384 (30%) had high/very high risk disease. Median follow-up time for the study was 6 years; 286 deaths occurred. The COD was CLL progression in 99 (35%), infection in 16 (6%), second malignancy in 47 (16%), CLL-unrelated in 59 (21%), and unknown in 65 (23%) patients. The rates of death due to CLL progression were higher (17.3% at 5 years; 30.3% at 10 years) than the rates due to CLL-related complications (5.7% at 5 years; 12.9% at 10 years) or due to CLL-unrelated causes (8.6% at 5 years; 16.9% at 10 years) in the CLL-IPI high/very high risk group, but not the CLL-IPI low or intermediate risk group (Table). A higher CLL-IPI risk group was associated with a higher rate of death due to CLL progression ( P < 0.001), as well as a higher rate of death due to CLL-related complications ( P = 0.013), and CLL-unrelated causes ( P < 0.001). Conclusions: Causes of death in newly diagnosed CLL patients differ according to their CLL-IPI risk group. In patients with high/very high risk CLL, improving CLL disease control with novel agents seems justified. In patients with low/intermediate risk CLL, there should be increased efforts to reverse immune dysfunction to reduce infections and second malignancies. [Table: see text]

Proposal of A Prognostic Score for Previously Untreated Patients with Chronic Lymphocytic Leukemia Based on An Overall Survival Analysis of Three German CLL Study Group Phase III Trials

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 2831-2831
Author(s):  
Jasmin Bahlo ◽  
Natali Pflug ◽  
Thomas Elter ◽  
Kathrin Bauer ◽  
Barbara Eichhorst ◽  
...  
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Risk Score ◽  
Research Funding ◽  
Prognostic Score ◽  
Phase Iii ◽  
Mutational Status ◽  
Phase Iii Trials ◽  
Binet Stage ◽  
Very High

Abstract Abstract 2831 Introduction Prognosis and need of treatment in CLL is currently determined by clinical staging systems of Binet and Rai. Recent research has focused on prognostic factors that may predict a poor prognosis independent of the clinical stage. Markers which have shown independent prognostic information are serum parameters and genetic factors (genomic aberrations, IgHV and p53 mutational status). To investigate the relevance of these different factors, we performed a pooled analysis using the data of three multicenter German CLL Study Group phase III trials (CLL1, CLL4 and CLL8). Based on this analysis we propose a prognostic score for previously untreated patients with early and advanced CLL. Material and Methods Patients were recruited between 1997 and 2006 into three phase III trials: 715 in CLL1 (“watch and wait” versus fludarabine (F)), 362 in CLL4 (F versus F and cyclophosphamide (FC)) and 817 patients in the CLL8 trial (FC versus FC and rituximab (FCR)). Serum parameters and genetic factors were centrally analyzed prior to treatment. The main end point of all statistical analyses was overall survival. First, univariate analyses were performed including variables of different groups such as baseline characteristics, stage of disease, laboratory results, molecular cytogenetics, mutational status and serum parameters. Next, multivariate Cox regressions were applied including all parameters that showed a significant association with overall survival in univariate analyses. To create a prognostic score we developed a weighted grading algorithm for independent factors based on ranges of hazard ratios. Finally, a prognostic score was defined as the sum of single ratings of adverse factors. According to this score, four different risk groups for overall survival could be identified. Results In total 1948 patients were eligible for the pooled analysis with a median age of 60 years (range, 30 to 81 years). After a median observation time of 63.4 months 485 deaths were reported. At study entry, 799 patients (42.4%) were at Binet stage A, 717 (38.0%) at Binet stage B and 370 (19.6%) at Binet stage C. Almost all considered variables were significantly associated with outcome and therefore included in the multivariate analysis. Based on the data of 1223 patients for whom all parameters were available, multivariate Cox regressions were performed and identified gender, age, ECOG score, del(17p), del(11q), IgHV mutational status, serum β2-microglobulin and serum thymidine kinase as independent factors for overall survival. Deletion 17p was the strongest adverse factor. Neither the clinical staging (Rai, Binet) nor the treatment modality were independent prognostic factors for overall survival. Similarly, the time interval between first diagnosis and study entry was not an independent prognostic factor. Due to the great differences between hazard ratios of independent factors, we developed a weighted grading system based on a simple algorithm to assign an individual grade to each adverse factor. By using this weighted grading, four different prognostic groups could be separated: low risk (score 0 – 2), intermediate risk (score 3 – 5), high risk (score 6 – 10) and very high risk (score 11 – 14) (figure 1). Overall survival rates were significantly different for these four groups with 95.2%, 86.9%, 67.7% and 18.7% survival after 5 years for the low, intermediate, high and very high risk group, respectively (p<0.0001). Moreover, within the group of patients showing a deletion 17p the score could distinguish patients of a high risk and a very high risk group (p<0.0001). Finally, the score could predict the individual risk for short overall survival independent of and within the different Binet or Rai stages (p<0.0001) (figure 2). Conclusion While Binet and Rai staging systems may remain important for the initial clinical assessment due to their simplicity, our prognostic score using a weighted combination of genetic and serum markers is superior to predict the overall survival of CLL patients. Disclosures: Pflug: Hoffmann-la Roche: Travel grant; Mundipharma: Travel grant. Eichhorst:Hoffmann La Roche: Honoraria, Research Funding, Travel Grants; Mundipharma: Research Funding, Travel Grants; Gilead: Consultancy. Bergmann:Celgene: Honoraria. Döhner:Hoffmann-la Roche: Research Funding. Stilgenbauer:Hoffmann La Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Travel Grants. Fischer:Hoffmann La Roche: Travel Grants. Hallek:Hoffmann-la Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees.

A New Prognostic Model for Extranodal Natural Killer/T Cell Lymphoma, Nasal Type

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 1769-1769
Author(s):  
Qingqing Cai ◽  
Xiaolin Luo ◽  
Ken H. Young ◽  
Huiqiang Huang ◽  
Guanrong Zhang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
High Risk ◽  
Prognostic Model ◽  
Cell Lymphoma ◽  
Prognostic Index ◽  
Roc Curves ◽  
Risk Groups ◽  
Survival Outcomes ◽  
Nasal Type

Abstract Background Extranodal natural killer (NK)/T–cell lymphoma, nasal type (ENKTL) is an aggressive disease with a poor prognosis. A better risk stratification is beneficial for clinical management in affected patients. Our recent study has shown that fasting blood glucose (FBG) was a novel, prognostic factor, (Cai et al, British Journal of Cancer, 108: 380–386,2013). This finding has not been integrated in the previous prognostic models for ENKTL Therefore, we aimed to design a new prognostic model, including FBG, for ENKTL which supports to identify high–risk patients eligible for advanced or more aggressive therapy. Patients and methods 158 newly diagnosed patients with ENKTL were analyzed between January 2003 and January 2011 at Sun Yat–sen University Cancer Center, China. Overall survival (OS) and progression free survival (PFS) were estimated using the Kaplan–Meier method. The significance of differences between survival was tested using the Log–rank test. Significant variables in the univariate analysis were selected as variables for the multivariate analysis of survival. The latter was performed by the Cox regression mode. We constructed receiver operating characteristic (ROC) curves and compared the areas under the ROC curves of total protein (TP), FBG, Korean Prognostic Index (KPI) and their combinations in comparison to the survival outcome. Results Of 158 patients, 156 patients had complete clinical information for the parameters of the International Prognostic Index (IPI) model and KPI model. The estimated 5–year overall survival rate in 158 patients was 59.2%. Independent prognostic factors included TP < 60 g/L, FBG > 100 mg/dL, KPI score ≥ 2. A new prognostic model was constructed by combining these prognostic factors: Group 1 (64 cases, 41.0%), no adverse factors; Group 2 (58 cases, 37.2%), one adverse factor; and Group 3 (34 cases, 21.8%), two or three adverse factors. The 5–year overall survival of these groups were 88.9%, 35.6% and 12.7%, respectively (p < 0.001). The survival curves according to the new prognostic model are shown in Fig. 1. The new model categorized three groups with significantly different survival outcomes. The new prognostic model was also efficient in discriminating the patients with low to low–intermediate risk IPI group and high–intermediate to high risk IPI group into three subgroups with different survival outcomes (p < 0.001). The KPI model balanced the distribution of patients into different risk groups better than IPI prognostic model (score 0: 12 cases, 7.7%; score 1: 38 cases, 24.4%; score 2: 42 cases, 26.9%; score 3–4: 64 cases, 41.0%), and it was able to differentiate patients with different survival outcomes (p < 0.001). In addition, the new prognostic model had a better prognostic value than did KPI model alone (p < 0.001), suggesting that TP and FBG reinforced the prognostic ability of KPI model (Table 1). Conclusions The new prognostic model we proposed for ENKTL, including the new prognostic indicator total protein and FBG, demonstrated balanced distribution of patients into different risk groups with better prognostic discrimination as compared to KPI model alone. Disclosures: No relevant conflicts of interest to declare.

Development of a stage-dependent prognostic model to predict psychosis in ultra-high-risk patients seeking treatment for co-morbid psychiatric disorders

2016 ◽  
Vol 46 (9) ◽  
pp. 1839-1851 ◽  
Author(s):  
H. K. Ising ◽  
S. Ruhrmann ◽  
N. A. F. M. Burger ◽  
J. Rietdijk ◽  
S. Dragt ◽  
...  
Keyword(s):  
High Risk ◽  
Social Functioning ◽  
Prognostic Model ◽  
Prognostic Index ◽  
First Episode Psychosis ◽  
Psychotic Symptoms ◽  
First Episode ◽  
Risk Class ◽  
Episode Psychosis ◽  
Ultra High Risk

BackgroundCurrent ultra-high-risk (UHR) criteria appear insufficient to predict imminent onset of first-episode psychosis, as a meta-analysis showed that about 20% of patients have a psychotic outcome after 2 years. Therefore, we aimed to develop a stage-dependent predictive model in UHR individuals who were seeking help for co-morbid disorders.MethodBaseline data on symptomatology, and environmental and psychological factors of 185 UHR patients (aged 14–35 years) participating in the Dutch Early Detection and Intervention Evaluation study were analysed with Cox proportional hazard analyses.ResultsAt 18 months, the overall transition rate was 17.3%. The final predictor model included five variables: observed blunted affect [hazard ratio (HR) 3.39, 95% confidence interval (CI) 1.56–7.35, p < 0.001], subjective complaints of impaired motor function (HR 5.88, 95% CI 1.21–6.10, p = 0.02), beliefs about social marginalization (HR 2.76, 95% CI 1.14–6.72, p = 0.03), decline in social functioning (HR 1.10, 95% CI 1.01–1.17, p = 0.03), and distress associated with suspiciousness (HR 1.02, 95% CI 1.00–1.03, p = 0.01). The positive predictive value of the model was 80.0%. The resulting prognostic index stratified the general risk into three risk classes with significantly different survival curves. In the highest risk class, transition to psychosis emerged on average ⩾8 months earlier than in the lowest risk class.ConclusionsPredicting a first-episode psychosis in help-seeking UHR patients was improved using a stage-dependent prognostic model including negative psychotic symptoms (observed flattened affect, subjective impaired motor functioning), impaired social functioning and distress associated with suspiciousness. Treatment intensity may be stratified and personalized using the risk stratification.

scholarly journals Allogeneic Transplant and CAR-T Therapy After Autologous Transplant Failure in DLBCL: A Noncomparative Cohort Analysis

2021 ◽  
Author(s):  
Mehdi Hamadani ◽  
Ajay K Gopal ◽  
Marcelo C. Pasquini ◽  
Soyoung Kim ◽  
Xianmiao Qiu ◽  
...  
Keyword(s):  
High Risk ◽  
Prognostic Model ◽  
Prognostic Score ◽  
Cohort Analysis ◽  
B Cell Lymphoma ◽  
Allogeneic Transplant ◽  
T Cell Therapy ◽  
Car T ◽  
Very High ◽  
Registry Analysis

Allogeneic transplant (alloHCT) and chimeric antigen receptor modified (CAR) T-cell therapy are potentially cuarative options of diffuse large B-cell lymphoma (DLBCL) relapsing after an autologous (auto) HCT. While the Center for International Blood and Marrow Transplant Research (CIBMTR) prognostic model can predict outcomes of alloHCT in DLBCL after autoHCT failure, corresponding models of CAR-T treatment in similar patient populations are not available. In this noncomparative registry analysis we report outcomes of DLBCL patients (≥18 years), undergoing a reduced intensity alloHCT or CAR-T therapy during 2012-2019, after a prior auto-HCT failure, and apply CIBMTR prognostic model to CAR-T recipients. 584 patients were included. The 1-year relapse, non-relapse mortality, overall survival (OS) and progression-free survival (PFS) for CAR-T treatment after autoHCT failure were were 39.5%, 4.8%, 73.4% and 55.7%, respectively. The corresponding rates in alloHCT cohort were 26.2%, 20.0%, 65.6% and 53.8%, respectively. The 1-year OS of alloHCT recipients classified as low-, intermediate- and high/very high-risk groups according to the CIBMTR prognostic score was 73.3%, 59.9%, and 46.3, respectively (p=0.002). The corresponding rates for low-, intermediate- and high/very high-risk CAR-T patients were 88.4%, 76.4%, and 52.8%, respectively (p&lt;0.001). This registry analysis shows that both CAR-T and alloHCT can provide durable remissions in subset of DLBCL patients relapsing after a prior autoHCT. The simple, CIBMTR prognostic score can be used to identify patients at high risk of treatment failure after either procedure. Evaluation of novel relapse mitigations strategies after cellular immunotherapies are warranted in these high risk patients.

Sign in / Sign up

Export Citation Format

Share Document