scholarly journals Five gene probes carry most of the discriminatory power of the 70-gene risk model in multiple myeloma

Leukemia ◽  
2014 ◽  
Vol 28 (12) ◽  
pp. 2410-2413 ◽  
Author(s):  
C J Heuck ◽  
P Qu ◽  
F van Rhee ◽  
S Waheed ◽  
S Z Usmani ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Risk Model ◽  
Discriminatory Power ◽  
Gene Probes

scholarly journals Prognostic model and immune-infiltrating cell landscape based on differentially expressed autophagy-related genes in TP53-mutated multiple myeloma

2021 ◽  
Author(s):  
Yan-Hua Zheng ◽  
Hong-Yuan Shen ◽  
Xiang Chen ◽  
Juan Feng ◽  
Guang-Xun Gao
Keyword(s):  
Multiple Myeloma ◽  
Prognostic Model ◽  
Risk Model ◽  
Predictive Accuracy ◽  
Area Under The Curve ◽  
Threshold Value ◽  
Differentially Expressed ◽  
Term Survival ◽  
Tp53 Mutations ◽  
Infiltrating Cells

IntroductionAutophagy functions as a prosurvival mechanism in multiple myeloma (MM).The objective of this research was to establish an autophagy-related gene (ARG) signature for predicting the survival outcomes of MM patients with TP53 mutations.Material and methodsInformation about MM patients with TP53 mutations was downloaded from Gene Expression Omnibus (GEO) database. Cox proportional hazard regression was employed to determine the independent prognostic ARG and construct a risk signature. Time-dependent receiver-operating characteristic (t ROC) curve was used to explore the predictive accuracy of the prognostic model. A nomogram was constructed to give a more precise prediction of the probability of 5-year, 8-year and 10-year overall survival (OS). In addition, we utilized the CIBERSORT algorithm to explore the distribution difference of 22 immune-infiltrating cells.ResultsThree differentially expressed ARGs (CASP8, MAPK8, RB1CC1) were finally incorporated to construct the risk model. Area under the curve (AUC) of corresponding tROC curve for 5-year,8-year and 10-year OS were 0.735, 0.686 and 0.662, respectively. MM patients were categorized into high and low-risk group in accordance with the median threshold value (-1.724549). ARG-based risk score model was an independent prognostic element correlated with OS, giving an hazard ratio (HR) of 3.29 (95%CI 2.35-4.60, P<0.001). 13 immune infiltrating cells were found to have distribution differences between the two groups.ConclusionsWe established a three-ARGs risk signature which manifested an independent prognostic factor. The nomogram was testified to perform well in forecasting the long-term survival of TP53-mutated MM patients.

scholarly journals The Prognostic Value of the m6A Score in Multiple Myeloma Based on Machine Learning

2021 ◽  
Vol 1 (3) ◽  
pp. 77-87
Author(s):  
Gong Xiao ◽  
Qiongjing Yuan ◽  
Wei Wang
Keyword(s):  
Multiple Myeloma ◽  
Cancer Progression ◽  
Risk Score ◽  
Prognostic Value ◽  
Risk Model ◽  
Cox Regression ◽  
Microarray Dataset ◽  
Immune Checkpoints ◽  
Bioinformatics Analyses ◽  
Cox Regression Analysis

Background: Multiple myeloma (MM) is one of the most common cancers of the blood system. N6-methyladenosine (m6A) plays an important role in cancer progression. We aimed to investigate the prognostic relevance of the m6A score in multiple myeloma through a series of bioinformatics analyses. Methods: The microarray dataset GSE4581 and GSE57317 used in this study were downloaded from the Gene Expression Omnibus (GEO) database. The m6A score was calculated using the GSVA package. The Random forests, univariate Cox regression analysis and Lasso analyses were performed for the differentially expressed genes (DEGs). Kaplan–Meier analysis and an ROC curve were used to diagnose the effectiveness of the model. Results: The GSVA R software package was used to predict the function. A total of 21 m6A genes were obtained, and 286 DEGs were identified between high and low m6A score groups. The risk model was constructed and composed of PRX, LBR, RB1, FBXL19-AS1, ARSK, MFAP3L, SLC44A3, UNC119 and SHCBP1. Functional analysis of risk score showed that with the increase in the risk score, Activated CD4 T cells, Memory B cells and Type 2 T helper cells were highly infiltrated. Conclusions: Immune checkpoints such as HMGB1, TGFB1, CXCL9 and HAVCR2 were significantly positively correlated with the risk score. We believe that the m6A score has a certain prognostic value in multiple myeloma.

Evaluation of Revised International Staging System for Transplant-Eligible Multiple Myeloma Patients

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 3452-3452
Author(s):  
Veronica Gonzalez-Calle ◽  
Abigail Slack ◽  
Susan Luft ◽  
Kathryn Pearce ◽  
Rhett P. Ketterling ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
High Risk ◽  
Partial Response ◽  
Renal Impairment ◽  
Research Funding ◽  
Risk Model ◽  
Independent Predictor ◽  
Staging System ◽  
Calcium Isotopes ◽  
International Staging System

Abstract Background: The current standard of care for eligible newly diagnosed multiple myeloma (MM) patients is induction therapy with novel agents followed by high dose chemotherapy and autologous stem cell transplant (ASCT). The International Myeloma Working Group proposed the Revised International Staging System (R-ISS) based on the presence of adverse chromosomal abnormalities (CA) detected by FISH (t(4;14), t(14;16) or del17p), in combination with ISS and LDH at diagnosis. However, there are a limited number of studies that have validated this risk model in the transplant and novel agents setting. Aims: To determine whether R-ISS is an appropriate risk-model for estimating overall survival (OS) and progression free survival (PFS) for transplant-eligible MM patients. Patients and Methods: We retrospectively studied a cohort of 519 MM patients who received novel drugs in the induction and subsequently underwent ASCT at Mayo Clinic Arizona from 2005 to 2014. In all, 95 patients met the inclusion criteria: comprising complete data at diagnosis (ISS, serum LDH level, and CA by FISH). The primary endpoint was OS from SCT and the secondary end point was PFS from ASCT. R-ISS groups were defined as described by Palumbo et al. J Clin Oncol. 2015; 33(26):2863-2869. Results: There were 50 (52.6%) men and 45 (47.4%) women who underwent ASCT in this period, with a median age at the time of transplant of 66-years-old (range, 36-78). There were 27 patients (28.4%) with high-risk CA: 12 patients (12.6%) with del17p; 11 patients (11.6%) with t(4;14); and 6 (6%) with t(14;16). In addition, 8 patients (8.5%) had high LDH levels and 9 patients (9.5%) presented with renal impairment at diagnosis. The patients were staged at diagnosis according to the three R-ISS groups: 44 patients (46.3%) had stage I, 26 (27.4%) had stage II, and 25 (26.3%) had stage III. CyBorD was the preferred induction regimen which was received by 42 patients (44%). There were 14 patients (15%) who received at least 2 lines of induction. All patients were in at least partial response (PR) at the moment of transplant: 32 in complete response (CR), 32 in very good partial response (VGPR) and the remaining 31 in PR. The response achieved at day +100 after ASCT improved, with 54 patients (57%) in CR, and only 18 patients (19%) in PR. After a median follow-up of 61 months (range, 14-135), median OS from SCT was 108 months (95% CI: 85 - 132 months) and the median PFS was 45.4 months (95% CI: 31.1 - 53.8 months) in the whole series.MM patients with R-ISS III had a significantly shorter median OS compared to patients with R-ISS II or R-ISS I (32.1 months vs. 94.7 months vs. not reached, respectively, P<0.0001) (Figure). No statistically significant differences in baseline characteristics were identified among these groups to explain the differences in OS observed. PFS among these groups was not statistically significant, only showing a trend towards shorter PFS in R-ISS III compared with either R-ISS I or II: median 22.1 months vs. 35.7 months, respectively, (P=0.2). Renal impairment at diagnosis, IgA subtype, ≥ 2 lines of induction treatment, and less than CR achieved at day +100 after ASCT were also associated with significantly inferior OS. Multivariate analysis selected R-ISS as an independent predictor for OS (HR: 2.3, 95% CI: 1.1-4.8; P=0.03), as well as ≥ 2 lines before ASCT. CR at day +100 after ASCT was the most important independent factor for predicting PFS (HR: 0.4; 95% CI: 0.2-0.6; P<0.001). Conclusion: R-ISS assessed at diagnosis was an independent predictor for OS after ASCT in our series, with median OS for the different R-ISS groups comparable to those reported by Palumbo et al. in their subgroup of younger patients. Thus, this study lends further support for the R-ISS as a reliable prognostic tool for estimating OS in transplant-eligible MM patients. In addition, new treatment approaches are needed for the high-risk patients (R-ISS III) with a median OS of 2.5 years. Figure Figure. Disclosures Reeder: Millennium: Research Funding; BMS: Research Funding; Celgene: Research Funding; Novartis: Research Funding. Mikhael:Abbvie: Research Funding; Onyx: Research Funding; Sanofi: Research Funding; Celgene: Research Funding. Bergsagel:Amgen, BMS, Novartis, Incyte: Consultancy; Novartis: Research Funding. Stewart:celgene: Consultancy. Fonseca:Janssen: Consultancy; Celgene: Consultancy; Sanofi: Consultancy; Novartis: Consultancy; Bayer: Consultancy; AMGEN: Consultancy; AMGEN: Consultancy; AMGEN: Consultancy; Patent: Patents & Royalties: Prognostication of MM based on genetic categorization of FISH of the disease; AMGEN: Consultancy; Millennium, a Takeda Company: Consultancy; Janssen: Consultancy; Sanofi: Consultancy; Patent Pending: Patents & Royalties: The use of calcium isotopes as biomarkers for bone metabolisms; Novartis: Consultancy; Patent: Patents & Royalties: Prognostication of MM based on genetic categorization of FISH of the disease; Millennium, a Takeda Company: Consultancy; Millennium, a Takeda Company: Consultancy; Bayer: Consultancy; Celgene: Consultancy; Patent Pending: Patents & Royalties: The use of calcium isotopes as biomarkers for bone metabolisms; Patent: Patents & Royalties: Prognostication of MM based on genetic categorization of FISH of the disease; Patent Pending: Patents & Royalties: The use of calcium isotopes as biomarkers for bone metabolisms; BMS: Consultancy; Millennium, a Takeda Company: Consultancy; BMS: Consultancy; Patent: Patents & Royalties: Prognostication of MM based on genetic categorization of FISH of the disease; Patent Pending: Patents & Royalties: The use of calcium isotopes as biomarkers for bone metabolisms.

Role of immune-related conditions in smoldering myeloma and MGUS.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 8104-8104 ◽  
Author(s):  
Mary Kwok ◽  
Neha Korde ◽  
Elisabet E. Manasanch ◽  
Manisha Bhutani ◽  
Irina Maric ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Bone Marrow ◽  
High Risk ◽  
Mayo Clinic ◽  
Plasma Cells ◽  
Risk Model ◽  
Expression Patterns ◽  
Autoimmune Disorder ◽  
Epidemiological Studies ◽  
Smoldering Myeloma

8104 Background: Recent guidelines emphasize tailored follow-up and the need for clinical trials for high-risk smoldering myeloma (SMM). Emerging evidence from epidemiological studies suggests that immune-related conditions play a role in the causation of myeloma precursor disease (SMM and monoclonal gammopathy of undetermined significance; MGUS) and are of clinical importance for the risk of developing multiple myeloma. The aim of our study is to assess whether there is an altered biology in SMM/MGUS patients with preceding immune-related conditions. Methods: From our ongoing prospective SMM/MGUS natural history study, we evaluated 56 SMM and 60 MGUS patients. Information on autoimmunity was identified at baseline. All patients underwent extensive clinical and molecular characterization. At baseline, all patients underwent bone marrow biopsy evaluation using immunohistochemistry and multi-color flow cytometry of plasma cells. We assessed expression patterns of adverse plasma cell markers (CD56 and CD117), and applied risk models based on serum immune markers and bone marrow findings. Results: Among enrolled SMM and MGUS patients, 7 (12%) and 9 (15%) had a preceding autoimmune disorder. We found SMM patients with (vs. without) a preceding autoimmune disorder to have a substantially lower rate of CD56 (28% vs. 61%) and CD117 (28% vs. 61%) expressing plasma cells. When we compared the same markers in MGUS patients, CD56 and CD117 expression patterns were similar among patients with vs. without preceding autoimmunity (10% vs. 17%, and 50% vs. 48%). Using the Mayo Clinic risk model, none of the SMM patients with a preceding autoimmune disorder had high-risk features; in contrast, 3/41 (7%) of those without a preceding autoimmune disorder were high-risk SMM. Using the Mayo Clinic risk model, none of the MGUS patients were high-risk independent of autoimmune status. Conclusions: Our prospective clinical study found SMM patients with preceding immune-related conditions to have less adverse biology, supportive of epidemiological studies suggesting the risk of developing multiple myeloma is substantially lower in these patients.

scholarly journals Identification of a three-gene-based prognostic model in multiple myeloma using bioinformatics analysis

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11320
Author(s):  
Ying Pan ◽  
Ye Meng ◽  
Zhimin Zhai ◽  
Shudao Xiong
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Normal Control ◽  
Prognostic Model ◽  
Risk Model ◽  
Cox Regression ◽  
Expression Profiles ◽  
Clinical Parameters ◽  
Hub Genes ◽  
Key Genes

Background Multiple myeloma (MM), the second most hematological malignancy, has high incidence and remains incurable till now. The pathogenesis of MM is poorly understood. This study aimed to identify novel prognostic model for MM on gene expression profiles. Methods Gene expression datas of MM (GSE6477, GSE136337) were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in GSE6477 between case samples and normal control samples were screened by the limma package. Meanwhile, enrichment analysis was conducted, and a protein-protein interaction (PPI) network of these DEGs was established by STRING and cytoscape software. Co-expression modules of genes were built by Weighted Correlation Network Analysis (WGCNA). Key genes were identified both from hub genes and the DEGs. Univariate and multivariate Cox congression were performed to screen independent prognostic genes to construct a predictive model. The predictive power of the model was evaluated by Kaplan–Meier curve and time-dependent receiver operating characteristic (ROC) curves. Finally, univariate and multivariate Cox regression analyse were used to investigate whether the prognostic model could be independent of other clinical parameters. Results GSE6477, including 101 case and 15 normal control, were screened as the datasets. A total of 178 DEGs were identified, including 59 up-regulated and 119 down-regulated genes. In WGCNA analysis, module black and module purple were the most relevant modules with cancer traits, and 92 hub genes in these two modules were selected for further analysis. Next, 47 genes were chosen both from the DEGs and hub genes as key genes. Three genes (LYVE1, RNASE1, and RNASE2) were finally screened by univariate and multivariate Cox regression analyses and used to construct a risk model. In addition, the three-gene prognostic model revealed independent and accurate prognostic capacity in relation to other clinical parameters for MM patients. Conclusion In summary, we identified and constructed a three-gene-based prognostic model that could be used to predict overall survival of MM patients.

scholarly journals Smoldering multiple myeloma: evolving diagnostic criteria and treatment strategies

Hematology ◽  
2021 ◽  
Vol 2021 (1) ◽  
pp. 673-681
Author(s):  
Alissa Visram ◽  
Joselle Cook ◽  
Rahma Warsame
Keyword(s):  
Multiple Myeloma ◽  
High Risk ◽  
Risk Stratification ◽  
Risk Model ◽  
Treatment Strategies ◽  
Progression Free Survival ◽  
Free Survival ◽  
Smoldering Myeloma ◽  
Insight Into ◽  
Made In

Abstract The adage for smoldering myeloma (SMM) has been to observe without treatment, until criteria for active multiple myeloma were satisfied. Definitions and risk stratification models have become more sophisticated, with prognostication tailored to include high-risk cytogenetics as per the most recent International Myeloma Working Group 2020 risk model. Moreover, progress in defining genomic evolution and changes in the bone marrow microenvironment through the monoclonal continuum have given insight into the complexities underlying the different patterns of progression observed in SMM. Given recent data showing improved progression-free survival with early intervention in high-risk SMM, the current dilemma is focused on how these patients should be treated. This case-based article maps the significant advancements made in the diagnosis and risk stratification of SMM. Data from landmark clinical trials will also be discussed, and ongoing trials are summarized. Ultimately, we outline our approach to SMM and hope to impart to the reader a sound concept of the current clinical management of SMM.

scholarly journals 47 Genes Define Myeloma Cell Acquired Resistance to Bortezomib and Have Profound Prognostic Implications in Multiple Myeloma

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 499-499
Author(s):  
Xenofon Papanikolaou ◽  
Caleb K. Stein ◽  
Ricky D Edmondson ◽  
Veronica Macleod ◽  
Ruslana Tytarenko ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Cell Lines ◽  
Myeloma Cell ◽  
Advisory Board ◽  
University Of Arkansas ◽  
Newly Diagnosed ◽  
Medical Sciences ◽  
Gene Probes ◽  
The Common

Abstract The proteasome inhibitor Bortezomib (Bz), the first agent of a new class of drugs in Multiple Myeloma (MM), has shown remarkable activity and forms an integral part of modern MM treatment. Nevertheless, resistance to Bz eventually develops in a significant proportion of patients, with adverse effects on survival. Numerous publications have addressed this issue through in vitro developed models of acquired Bz resistance (BzR). However the results were quite different in each publication, none of the produced Bz myeloma cell lines was provably stable, no common mechanism of resistance could be demonstrated, and hence were of minimal relevance to the clinical setting. In order to address these issues an effort was made for the development of an in vitro model of acquired BzR that would resemble the clinical reality in the most accurate way. Two myeloma cell lines were used, one resembling a multisensitive (JJN3) and the other a multiresistant (U266) drug behavior, that were both sensitive to Bz. An at least 20 fold increase in the 48h Bz IC50 was noted for both cell lines. The increase in the IC50 was able to be verified a year after culturing the cell lines in normal medium thus ensuring a stable resistance phenotype. To delineate the molecular mechanisms that underlie the development of BzR a combined genetic/Gene Expression Profile (GEP) and functional/Proteomics approach was used with emphasis in the common elements of both cell lines. The hypothesis was that if certain pathways are activated in the cells that actually produce the phenotype of BzR they must fulfil two important criteria: 1) They must be present in all the levels of the BzR, 2) The gene changes have to be verified in the level of the gene encoded proteins thus securing their functional importance. GEP of the naïve cell lines along with the GEP of the Bz resistant cells at different levels of BzR (5-fold, 10-fold, 20-fold) were used. The statistical analysis revealed 100 gene probes common in both cell lines that achieved their highest change as soon as BzR was established and remained stable at that level for all later versions (P<0.1, q<0.1) and 115 gene probes common in both cell lines that their change was proportional to the level of BzR (P<0.001, q <0.005). The proteomics analysis of the Bz resistant cell lines at their latest level of resistance (20-fold) revealed 262 proteins common in both cell lines that were up-regulated and 263 common in both cell lines that were down-regulated (change >10% to be considered significant). The intersection of the list of the common genes with the list of the common proteins revealed 47 gene-proteins all but one novel in MM. They can be grouped in distinct biological categories with the most prominent ones being the ROS/Mitochondrial Factor category comprising of 10 gene-proteins, the E3 Ubiquitin Pathway 6 genes-proteins and Translation Regulation 5 genes-proteins. Even more importantly 30 of them have profound survival implications in MM -all of them novel in MM- both for Overall Survival (OS) and Progression Free Survival (PFS) in both Bz (TT3) and non Bz (TT2) containing protocols implying that myeloma cells apply both Bz specific and non-specific mechanisms to acquire BzR. Based on these 30 genes-proteins a GEP risk score (GEP-30) was constructed that was able to achieve remarkable statistical power in both Bz containing and non containing trials of both newly diagnosed (TT2 with and without thalidomide i.e. TT2+ and TT2-, TT3a, TT3b, HOVON, MRC IX, Figure 1A,B,C) and relapsed MM (TT6 , OS: NR vs 1.52 yr P<0.00001, PFS: NR vs 1.13 yr P<0.00001 for low and high risk) Figure 1. KM plots for OS and PFS of GEP-30 for newly diagnosed MM Figure 1. KM plots for OS and PFS of GEP-30 for newly diagnosed MM Figure 1B. Figure 1B. Figure 1C. Figure 1C. Disclosures Stein: University of Arkansas for Medical Sciences: Employment. Barlogie:University of Arkansas for Medical Sciences: Employment. Epstein:University of Arkansas for Medical Sciences: Employment. Heuck:Janssen: Other: Advisory Board; Celgene: Consultancy; Millenium: Other: Advisory Board; Foundation Medicine: Honoraria; University of Arkansas for Medical Sciences: Employment.

Development and Validation of a Risk Assessment Model for Early Infection during the First 3 Months in Patients with Newly Diagnosed Multiple Myeloma

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 29-30
Author(s):  
Yufeng Shang ◽  
Weida Wang ◽  
Minghui Liu ◽  
Xiaoqin Chen ◽  
Zhongjun Xia ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
High Risk ◽  
Model Building ◽  
Risk Model ◽  
Conflicts Of Interest ◽  
Treatment Strategies ◽  
Risk Groups ◽  
Assessment Model ◽  
Early Infection ◽  
Lasso Regression

PurposeEarly infection was an important cause of mortality in patients with multiple myeloma (MM). The study aimed to assess factors affecting early infection and identify patients with high risk developing infection. MethodsDuring January 2010 to June 2019, patients with MM were analyzed, retrospectively. The data was divided into training and independent validation cohort. The least absolute shrinkage and selection operator (LASSO) regression model was used for data dimension reduction, feature selection, and model building. ResultsOf 745 confirmed MM patients, 540 eligible cases were included in final analyses. In total, 165 patients (30.6%) suffered infections, while 110 patients (20.4%) occurred early infections during the first 3 months after diagnosis. Bacteria and the respiratory tract were the most common pathogen and localization of infection, respectively. In training cohort, PS≥2, HGB&lt;100g/L, β2MG≥6.0mg/L and GLB≥80g/L were identified associated with early infections by LASSO regression. Based on the four factors, an early infection risk model of MM (IRMM) was established to define high- and low-risk groups, which showed significantly different rates of infection (35.3% vs. 9.4%,P&lt;0.001, HR=4.381 [95% CI, 2.802-7.221]). IRMM displayed good discrimination (AUC=0.756) and calibration (P=0.94). ConclusionWe determined risk factors for early infection and established a predictive model to help clinicians identify patients with high-risk infection. It can help clinicians to determine whether to adjust monitoring and treatment strategies, or apply prophylactic interventions to high-risk patients. Disclosures No relevant conflicts of interest to declare.

Development, Prediction, and Treatment of Anemia in Patients (pts) with Lymphoma/Multiple Myeloma (L/M): Findings of Two European Surveys (ECAS and BEPOS).

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 3133-3133
Author(s):  
Heinz Ludwig ◽  
Simon Van Belle ◽  
Pere Gascón
Keyword(s):  
At Risk ◽  
Multiple Myeloma ◽  
Treatment Initiation ◽  
Risk Model ◽  
Predictive Accuracy ◽  
Hematologic Malignancy ◽  
Performance Status ◽  
Female Gender ◽  
Mean Time ◽  
Anemia Treatment

Abstract Quality of life (QOL) in cancer pts is adversely affected by several factors, including disease- or treatment-related anemia. Between January 2001 and February 2002, the European Cancer Anaemia Survey (ECAS) was conducted to provide information on pervasiveness of cancer-related anemia, impact of anemia on WHO performance status, risk factors for its development, and anemia treatment practices in Europe. Briefly, a total of 15,370 pts were enrolled, of whom 2,360 had L/M. Data analysis showed 53% of L/M pts were anemic (hemoglobin [Hb] &lt;12 g/dL) at enrollment and 73% were anemic at some time during the survey. Low Hb levels correlated significantly with WHO performance scores of 3 or 4 (P &lt;0.001, R =.352). The ECAS data were additionally analyzed to determine patient and disease characteristics that predicted anemia development and to construct a model for identifying pts at risk. Using logistic regression on the L/M incidence group (pts who were not anemic and not being treated for cancer at enrollment, started chemotherapy [CT] during ECAS, and had at least 2 CT cycles during the survey), 4 variables were found to significantly predict anemia development. Initial Hb, persistent/recurrent disease, female gender, and intent to treat or treatment with platinum-based CT were found to independently predict anemia (P &lt;0.001), with an area under the ROC curve of 0.821 (95% CI; 0.763–0.878), indicating acceptable predictive accuracy of the model. Three levels of risk (low [24%], moderate [51%], and high [72%]) for developing anemia were calculated from the model (χ2(2) = 112.6, P &lt;0.001). Mean time required for anemia development was 9.0 wks to reach Hb of &lt;12 g/dL, 11.1 wks to reach Hb of &lt;11 g/dL, and 13.3 wks to reach Hb of &lt;10 g/dL. Notably, only 46% of anemic L/M pts received anemia treatment. Subsequently, a recent (2003) survey, the Belgian Erythropoietin Survey (BEPOS), extended the information gained through ECAS by examining use of recombinant human erythropoietin (rHuEPO) in pts receiving CT. Specifically, BEPOS documented when rHuEPO treatment was started, dosing schedules and dosage adjustments, length of treatment, impact of iron supplementation on rHuEPO treatment, and outcomes. Patients enrolled had either solid tumors (non-small-cell lung cancer, breast cancer) or hematologic malignancies (multiple myeloma [MM], Hodgkin’s disease [HD], non-Hodgkin’s lymphoma [NHL]). Interim results suggest that 72% of BEPOS pts began rHuEPO during the first 2 CT cycles, with an overall median Hb value of 10.1 g/dL at treatment initiation. For hematologic malignancy pts, the median Hb at treatment initiation was ~10 g/dL for HD; in NHL and MM, the median Hb was &gt;9 to &lt;10 g/dL. Mean time for all pts to achieve a 2-g/dL increase in Hb in the absence of transfusion was 6.4 wks; mean time for NHL pts (6.3 wks) was similar, while mean time for MM pts (9.1 wks) was longer, more in line with that seen in clinical trials. Achievement of the 2-g/dL increase in Hb after 6.4 wks determined in BEPOS is consistent with increases of ~1 g/dL after 4 wks and ~2 g/dL after 8 wks noted in studies of epoetin alfa (Demetri 1998, Gabrilove 2001, Littlewood 2001). Using the large ECAS database, an anemia risk model has been established that should help identify pts at risk for anemia, so that administration of rHuEPO can be initiated expeditiously, before Hb declines to considerably lower levels and/or anemia symptoms, including impaired QOL, develop.

Discriminatory Power of RAPD,PCR-RFLP and Southern Blot Analyses of ureCD or ureA Gene Probes on Helicobacter pylori Isolates

2002 ◽  
Vol 57 (5-6) ◽  
pp. 516-521 ◽  
Author(s):  
Stella Smith ◽  
Franck Cantet ◽  
Fabrice Angelini ◽  
Armelle Marais ◽  
Francis Mégraud ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Helicobacter Pylori ◽  
Southern Blot ◽  
Blot Analysis ◽  
Southern Blot Analysis ◽  
Discriminatory Power ◽  
Gene Probes ◽  
Rapd Pcr ◽  
Pcr Rflp

The genetic diversity of 33 Nigerian Helicobacter pylori isolates were studied using RAPD, PCR-RFLP and Southern blot analysis of ureA or ureCD gene probes. RAPD was able to distinguish the following number of isolates using the primers 3880 : 5ʹ-AAGAGCCCGT-3ʹ (28), 3881 :5ʹ-AACGCGCAAC-3ʹ (33) and OPH8 :5ʹ-GAAACACCCC-3ʹ (25). Southern blot analysis using the ureCD probe was also able to distinguish the 12 isolates tested into ten different patterns. The PCR-RFLP technique distinguished all 33 isolates into six types. In conclusion, considering typeability, discriminatory power, and convenience, RAPD with the 3881 primer was considered the most useful technique.

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