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  • 2000-2004  (6)
  • 1985-1989  (1)
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  • 1
    Monograph available for loan
    Monograph available for loan
    Washington D.C.
    Call number: PIK W 100-99-0206
    Type of Medium: Monograph available for loan
    Pages: 336 p.
    Branch Library: PIK Library
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  • 2
    Electronic Resource
    Electronic Resource
    Berkeley, Calif. : Berkeley Electronic Press (now: De Gruyter)
    Statistical applications in genetics and molecular biology 3.2004, 1, art10 
    ISSN: 1544-6115
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: Motivation: Standard laboratory classification of the plasma cell dyscrasia monoclonal gammopathy of undetermined significance (MGUS) and the overt plasma cell neoplasm multiple myeloma (MM) is quite accurate, yet, for the most part, biologically uninformative. Most, if not all, cancers are caused by inherited or acquired genetic mutations that manifest themselves in altered gene expression patterns in the clonally related cancer cells. Microarray technology allows for qualitative and quantitative measurements of the expression levels of thousands of genes simultaneously, and it has now been used both to classify cancers that are morphologically indistinguishable and to predict response to therapy. It is anticipated that this information can also be used to develop molecular diagnostic models and to provide insight into mechanisms of disease progression, e.g., transition from healthy to benign hyperplasia or conversion of a benign hyperplasia to overt malignancy. However, standard data analysis techniques are not trivial to employ on these large data sets. Methodology designed to handle large data sets (or modified to do so) is needed to access the vital information contained in the genetic samples, which in turn can be used to develop more robust and accurate methods of clinical diagnostics and prognostics.Results: Here we report on the application of a panel of statistical and data mining methodologies to classify groups of samples based on expression of 12,000 genes derived from a high density oligonucleotide microarray analysis of highly purified plasma cells from newly diagnosed MM, MGUS, and normal healthy donors. The three groups of samples are each tested against each other. The methods are found to be similar in their ability to predict group membership; all do quite well at predicting MM vs. normal and MGUS vs. normal. However, no method appears to be able to distinguish explicitly the genetic mechanisms between MM and MGUS. We believe this might be due to the lack of genetic differences between these two conditions, and may not be due to the failure of the models. We report the prediction errors for each of the models and each of the methods. Additionally, we report ROC curves for the results on group prediction. Availability: Logistic regression: standard software, available, for example in SAS. Decision trees and boosted trees: C5.0 from www.rulequest.com. SVM: SVM-light is publicly available from svmlight.joachims.org. Naïve Bayes and ensemble of voters are publicly available from www.biostat.wisc.edu/~mwaddell/eov.html. Nearest Shrunken Centroids is publicly available from http://www-stat.stanford.edu/~tibs/PAM.
    Type of Medium: Electronic Resource
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  • 3
    Publication Date: 2002-05-01
    Description: The role of maintenance therapy in multiple myeloma is controversial. Recent studies have shown an improvement in both progression-free and overall survival for patients receiving maintenance treatment with a combination of interferon and glucocorticoids, compared with interferon alone. The role of glucocorticoids alone as maintenance therapy has not been previously addressed. We compared alternate-day, oral prednisone at 2 different dose levels (10 mg versus 50 mg) for remission maintenance among previously untreated myeloma patients following a response to induction with standard-dose vincristine, doxorubicin, and dexamethasone with prednisone (VAD-P) or VAD-P plus quinine (VAD-P/Q). There were 250 eligible patients registered on Southwest Oncology Group study 9210 and randomized to receive VAD-P or VAD-P/Q. There were 125 patients achieving at least a 25% tumor reduction following induction therapy who were randomized to either physiologic (10 mg) or pharmacologic (50 mg) doses of alternate-day, oral prednisone until disease progression. At the time of study entry, patient characteristics were similar in VAD-P and VAD-P/Q patients and in the 2 arms randomized to maintenance therapy. After a median follow-up of 53 months, there was no difference in either progression-free or overall survival between the 2 induction regimens. However, from the time of maintenance randomization, both progression-free (14 versus 5 months; P = .003) and overall survival (37 versus 26 months; P = .05) were significantly improved in patients receiving 50 mg as compared with 10 mg alternate-day prednisone. There was no difference in treatment-related adverse events between the groups. Thus, 50 mg, oral, alternate-day prednisone is effective maintenance treatment for multiple myeloma patients who achieve a response to induction chemotherapy.
    Print ISSN: 0006-4971
    Electronic ISSN: 1528-0020
    Topics: Biology , Medicine
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  • 4
    Publication Date: 2004-12-01
    Description: Current therapy of primary systemic (AL) amyloidosis with oral melphalan and prednisone remains unsatisfactory, with a median survival of only 13 months. Between 1996 and 2003, 93 patients with biopsy-proven AL amyloidosis were enrolled in a prospective US national cooperative group trial. Treatment schema consisted of induction therapy with pulse dexamethasone (DEX), followed by maintenance therapy with DEX and alpha interferon. Hematologic complete remissions were observed in 24% and improvement in AL amyloidosis–related organ dysfunction occurred in 45% of patients evaluable for response. Median survival of the entire cohort is 31 months, with an estimated 2-year overall survival (OS) and event-free survival (EFS) of 60% and 52%, respectively. Presence of congestive heart failure and increased level of serum β2 microglobulin (≥ 0.0035 g/L [3.5 mg/L]) were dominant predictors of adverse outcome. Estimated 2-year OS in patients who are eligible to receive transplants with this approach was 78%. These data demonstrate for the first time in the context of a US multicenter prospective clinical trial that front-line therapy with a DEX-based regimen in AL amyloidosis can lead to durable reversal of AL amyloidosis–related organ dysfunction and prolonged survival.
    Print ISSN: 0006-4971
    Electronic ISSN: 1528-0020
    Topics: Biology , Medicine
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  • 5
    Publication Date: 2001-07-01
    Description: Current information on Waldenström macroglobulinemia (WM) is based on retrospective or single-institution studies of patients requiring therapy. Between 1992 and 1998, 231 patients with WM were enrolled in a prospective observational multicenter clinical trial. Of these, 182 patients with symptomatic or progressive disease were treated with 4 to 8 cycles of therapy with a purine nucleoside analogue, fludarabine (FAMP; 30 mg/m2 of body-surface area daily for 5 days every 28 days). A serum β2-microglobulin (β2M) level below 3 mg/L and a hemoglobin level of at least 120 g/L (12 g/dL) at presentation predicted a lower likelihood of requiring therapy. The overall rate of response to FAMP therapy was 36% (95% confidence interval, 29%-44%), with 2% complete remissions. Patients who were 70 years old or older had a substantially lower likelihood of response (odds ratio, 0.34; P = .004) than younger patients. On multivariate analysis, a serum β2M level of 3 mg/L or higher, hemoglobin level below 120 g/L, and serum IgM level below 40 g/L [4 g/dL] were significant adverse prognostic factors for survival. We developed a simple staging system for WM by using these variables and identified 4 distinct subsets of patients with estimated 5-year overall survival rates of 87%, 64%, 53%, and 22%, and 5-year progression-free survival rates of 83%, 55%, 33%, and 12%. Prognosis in WM is highly variable and serum β2M was the dominant predictor of a need for therapy and of survival. FAMP has activity against WM. Our staging system may provide guidance for a risk-based approach to the treatment of WM.
    Print ISSN: 0006-4971
    Electronic ISSN: 1528-0020
    Topics: Biology , Medicine
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  • 6
    Publication Date: 2004-11-16
    Description: Extreme Regression (LeBlanc, Moon and Kooperberg, manuscript submitted) is a statistical technique for finding patient subsets with either very good or very poor prognosis. In contrast to Cox regression, which generates predictions based on linear combinations of variables, Extreme Regression results in groups based on intersections or unions of simple statements involving single covariates (eg sb2m 〉 3.5 and albumin 〈 3.5; sb2m 〉 3.5 or LDH 〉 ULN). Thus, Extreme Regression is similar in spirit to tree-based regression methods, except that the goal is not to develop a complete staging system (like the new International Staging System, ISS, for myeloma, which was derived using tress-based methods) but rather to define subsets of a given size (eg 10%) with extreme prognosis. Here prognosis may be defined in terms of any type of outcome such as response, one-year mortality, overall survival, etc. To illustrate we use survival data from the Intergroup Trial S9321, which tested high dose therapy with melphalan and TBI versus a standard dose regimen of VBMCP (both after VAD induction) for newly diagnosed patients with multiple myeloma. We used as potential predictors serum beta-2 microglobulin (sb2m), LDH, albumin and creatinine as measured at baseline. There were 682 eligible patients with complete data on these four covariates. We asked the algorithm to identify roughly 10% of the patients representing a poor prognosis group, and then another 25% representing a good prognosis group. The results are shown in Figure 1, along with the intermediate group of all other patients. The poor risk group comprised 77 patients (11% of the total) and was defined by those patients with sb2m 〉 9 and LDH 〉 ULN; or patients with creatinine 〉 5; or patients with albumin 〈 2. These patients had a median survival of 19 months, a one year survival of 66%, and a five year survival of 19%. The good risk group included 181 patients (27%) defined by LDH
    Print ISSN: 0006-4971
    Electronic ISSN: 1528-0020
    Topics: Biology , Medicine
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  • 7
    Publication Date: 2004-01-08
    Description: Motivation: Standard laboratory classification of the plasma cell dyscrasia monoclonal gammopathy of undetermined significance (MGUS) and the overt plasma cell neoplasm multiple myeloma (MM) is quite accurate, yet, for the most part, biologically uninformative. Most, if not all, cancers are caused by inherited or acquired genetic mutations that manifest themselves in altered gene expression patterns in the clonally related cancer cells. Microarray technology allows for qualitative and quantitative measurements of the expression levels of thousands of genes simultaneously, and it has now been used both to classify cancers that are morphologically indistinguishable and to predict response to therapy. It is anticipated that this information can also be used to develop molecular diagnostic models and to provide insight into mechanisms of disease progression, e.g., transition from healthy to benign hyperplasia or conversion of a benign hyperplasia to overt malignancy. However, standard data analysis techniques are not trivial to employ on these large data sets. Methodology designed to handle large data sets (or modified to do so) is needed to access the vital information contained in the genetic samples, which in turn can be used to develop more robust and accurate methods of clinical diagnostics and prognostics.Results: Here we report on the application of a panel of statistical and data mining methodologies to classify groups of samples based on expression of 12,000 genes derived from a high density oligonucleotide microarray analysis of highly purified plasma cells from newly diagnosed MM, MGUS, and normal healthy donors. The three groups of samples are each tested against each other. The methods are found to be similar in their ability to predict group membership; all do quite well at predicting MM vs. normal and MGUS vs. normal. However, no method appears to be able to distinguish explicitly the genetic mechanisms between MM and MGUS. We believe this might be due to the lack of genetic differences between these two conditions, and may not be due to the failure of the models. We report the prediction errors for each of the models and each of the methods. Additionally, we report ROC curves for the results on group prediction.Availability: Logistic regression: standard software, available, for example in SAS. Decision trees and boosted trees: C5.0 from www.rulequest.com. SVM: SVM-light is publicly available from svmlight.joachims.org. Naïve Bayes and ensemble of voters are publicly available from www.biostat.wisc.edu/~mwaddell/eov.html. Nearest Shrunken Centroids is publicly available from http://www-stat.stanford.edu/~tibs/PAM.
    Electronic ISSN: 1544-6115
    Topics: Biology
    Published by De Gruyter
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