Y-90 Ibritumomab Tiuxetan (Zevalin (R)) Consolidation of First Remission In Advanced Stage Follicular Non Hodgkin's Lymphoma Updated Results After a Median Follow up of 662 Months From the International, Randomized, Phase III First Line Indolent Trial (FIT) In 414 Patients

The FIT trial was conducted to evaluate the safety and efficacy of 90Y-ibritumomab tiuxetan (0.4 mCi/kg; maximum dose 32 mCi) when used as consolidation of first complete or partial remission in patients with previously untreated, advanced-stage follicular lymphoma (FL). Patients were randomly assigned to either 90Y-ibritumomab treatment (n = 207) or observation (n = 202) within 3 months (mo) of completing initial induction therapy (chemotherapy only: 86%; rituximab in combination with chemotherapy: 14%). Response status prior to randomization did not differ between the groups: 52% complete response (CR)/CR unconfirmed (CRu) to induction therapy and 48% partial response (PR) in the 90Y-ibritumomab arm vs 53% CR/CRu and 44% PR in the control arm. The primary endpoint was progression-free survival (PFS) of the intent-to-treat (ITT) population. Results from the first extended follow-up after a median of 3.5 years revealed a significant improvement in PFS from the time of randomization with 90Y-ibritumomab consolidation compared with control (36.5 vs 13.3 mo, respectively; P < 0.0001; Morschhauser et al. JCO. 2008; 26:5156-5164). Here we report a median follow-up of 66.2 mo (5.5 years). Five-year PFS was 47% in the 90Y-ibritumomab group and 29% in the control group (hazard ratio (HR) = 0.51, 95% CI 0.39-0.65; P < 0.0001). Median PFS in the 90Y-ibritumomab group was 49 mo vs 14 mo in the control group. In patients achieving a CR/CRu after induction, 5-year PFS was 57% in the 90Y-ibritumomab group, and the median had not yet been reached at 92 months, compared with a 43% 5-year PFS in the control group and a median of 31 mo (HR = 0.61, 95% CI 0.42-0.89). For patients in PR after induction, the 5-year PFS was 38% in the 90Y-ibritumomab group with a median PFS of 30 mo vs 14% in the control group with a median PFS of 6 mo (HR = 0.38, 95% CI 0.27-0.53). Patients who had received rituximab as part of induction treatment had a 5-year PFS of 64% in the 90Y-ibritumomab group and 48% in the control group (HR = 0.66, 95% CI 0.30-1.47). For all patients, time to next treatment (as calculated from the date of randomization) differed significantly between both groups; median not reached at 99 mo in the 90Y-ibritumomab group vs 35 mo in the control group (P < 0.0001). The majority of patients received rituximab-containing regimens when treated after progression (63/82 [77%] in the 90Y-ibritumomab group and 102/122 [84%] in the control group). Overall response rate to second-line treatment was 79% in the 90Y-ibritumomab group (57% CR/CRu and 22% PR) vs 78% in the control arm (59% CR/CRu, 19% PR). Five-year overall survival was not significantly different between the groups; 93% and 89% in the 90Y-ibritumomab and control groups, respectively (P = 0.561). To date, 40 patients have died; 18 in the 90Y-ibritumomab group and 22 in the control group. Secondary malignancies were diagnosed in 16 patients in the 90Y-ibritumomab arm vs 9 patients in the control arm (P = 0.19). There were 6 (3%) cases of myelodysplastic syndrome (MDS)/acute myelogenous leukemia (AML) in the 90Y-ibritumomab arm vs 1 MDS in the control arm (P = 0.063). In conclusion, this extended follow-up of the FIT trial confirms the benefit of 90Y-ibritumomab consolidation with a nearly 3 year advantage in median PFS. A significant 5-year PFS improvement was confirmed for patients with a CR/CRu or a PR after induction. Effective rescue treatment with rituximab-containing regimens may explain the observed no difference in overall survival between both patient groups who were - for the greater part - rituximab-naïve.

Modern statistical models for forensic fingerprint examinations : a critical review

Over the last decade, the development of statistical models in support of forensic fingerprint identification has been the subject of increasing research attention, spurned on recently by commentators who claim that the scientific basis for fingerprint identification has not been adequately demonstrated. Such models are increasingly seen as useful tools in support of the fingerprint identification process within or in addition to the ACE-V framework. This paper provides a critical review of recent statistical models from both a practical and theoretical perspective. This includes analysis of models of two different methodologies: Probability of Random Correspondence (PRC) models that focus on calculating probabilities of the occurrence of fingerprint configurations for a given population, and Likelihood Ratio (LR) models which use analysis of corresponding features of fingerprints to derive a likelihood value representing the evidential weighting for a potential source.

Using 3D surface datasets to understand landslide evolution: From analogue models to real case study

Early detection of landslide surface deformation with 3D remote sensing techniques, as TLS, has become a great challenge during last decade. To improve our understanding of landslide deformation, a series of analogue simulation have been carried out on non-rigid bodies coupled with 3D digitizer. All these experiments have been carried out under controlled conditions, as water level and slope angle inclination. We were able to follow 3D surface deformation suffered by complex landslide bodies from precursory deformation still larger failures. These experiments were the basis for the development of a new algorithm for the quantification of surface deformation using automatic tracking method on discrete points of the slope surface. To validate the algorithm, comparisons were made between manually obtained results and algorithm surface displacement results. Outputs will help in understanding 3D deformation during pre-failure stages and failure mechanisms, which are fundamental aspects for future implementation of 3D remote sensing techniques in early warning systems.

Phase III trial of consolidation therapy with yttrium-90-ibritumomab tiuxetan compared with no additional therapy after first remission in advanced follicular lymphoma.

PURPOSE: We conducted an international, randomized, phase III trial to evaluate the efficacy and safety of consolidation with yttrium-90 ((90)Y)-ibritumomab tiuxetan in patients with advanced-stage follicular lymphoma in first remission. PATIENTS AND METHODS: Patients with CD20(+) stage III or IV follicular lymphoma, who achieved a complete response (CR)/unconfirmed CR (CRu) or partial response (PR) after first-line induction treatment, were randomly assigned to receive (90)Y-ibritumomab tiuxetan (rituximab 250 mg/m(2) on day -7 and day 0 followed on day 0 by (90)Y-ibritumomab tiuxetan 14.8 MBq/kg; maximum of 1,184 MBq) or no further treatment (control). The primary end point was progression-free survival (PFS), which was calculated from the time of random assignment. RESULTS: A total of 414 patients (consolidation, n = 208; control, n = 206) were enrolled at 77 centers. (90)Y-ibritumomab tiuxetan consolidation significantly prolonged median PFS (after a median observation time of 3.5 years) in all patients (36.5 v 13.3 months in control arm; hazard ratio [HR] = 0.465; P &lt; .0001) and regardless of whether patients achieved PR (29.3 v 6.2 months in control arm; HR = 0.304; P &lt; .0001) or CR/CRu (53.9 v 29.5 months in control arm; HR = 0.613; P = .0154) after induction treatment. Median PFS with consolidation was prolonged in all Follicular Lymphoma International Prognostic Index risk subgroups. After (90)Y-ibritumomab tiuxetan consolidation, 77% of patients in PR after induction converted to CR/CRu, resulting in a final CR rate of 87%. The most common toxicity with (90)Y-ibritumomab tiuxetan was hematologic, and grade 3 or 4 infections occurred in 8% of patients. CONCLUSION: Consolidation of first remission with (90)Y-ibritumomab tiuxetan in advanced-stage follicular lymphoma is highly effective with no unexpected toxicities, prolonging PFS by 2 years and resulting in high PR-to-CR conversion rates regardless of type of first-line induction treatment.

Chemotherapy for advanced gastric cancer.

BACKGROUND: Gastric cancer currently ranks second in global cancer mortality. Most patients are either diagnosed at an advanced stage, or develop a relapse after surgery with curative intent. Apart from supportive care and palliative radiation to localized (e.g. bone) metastasis, systemic chemotherapy is the only treatment option available in this situation. OBJECTIVES: To assess the efficacy of chemotherapy versus best supportive care, combination versus single agent chemotherapy and different combination chemotherapy regimens in advanced gastric cancer. SEARCH STRATEGY: We searched the Cochrane Central Register of Controlled Trials, MEDLINE and EMBASE up to March 2009, reference lists of studies, and contacted pharmaceutical companies and national and international experts. SELECTION CRITERIA: Randomised controlled trials on systemic intravenous chemotherapy versus best supportive care, combination versus single agent chemotherapy and different combination chemotherapies in advanced gastric cancer. DATA COLLECTION AND ANALYSIS: Two authors independently extracted data. A third investigator was consulted in case of disagreements. We contacted study authors to obtain missing information. MAIN RESULTS: Thirty five trials, with a total of 5726 patients, have been included in the meta-analysis of overall survival. The comparison of chemotherapy versus best supportive care consistently demonstrated a significant benefit in overall survival in favour of the group receiving chemotherapy (hazard ratios (HR) 0.37; 95% confidence intervals (CI) 0.24 to 0.55, 184 participants). The comparison of combination versus single-agent chemotherapy provides evidence for a survival benefit in favour of combination chemotherapy (HR 0.82; 95% CI 0.74 to 0.90, 1914 participants). The price of this benefit is increased toxicity as a result of combination chemotherapy. When comparing 5-FU/cisplatin-containing combination therapy regimens with versus without anthracyclines (HR 0.77; 95% CI 0.62 to 0.95, 501 participants) and 5-FU/anthracycline-containing combinations with versus without cisplatin (HR 0.82; 95% CI 0.73 to 0.92, 1147 participants) there was a significant survival benefit for regimens including 5-FU, anthracyclines and cisplatin. Both the comparison of irinotecan versus non-irinotecan (HR 0.86; 95% CI 0.73 to 1.02, 639 participants) and docetaxel versus non-docetaxel containing regimens (HR 0.93; 95% CI 0.75 to 1.15, 805 participants) show non-significant overall survival benefits in favour of the irinotecan and docetaxel-containing regimens. AUTHORS' CONCLUSIONS: Chemotherapy significantly improves survival in comparison to best supportive care. In addition, combination chemotherapy improves survival compared to single-agent 5-FU. All patients should be tested for their HER-2 status and trastuzumab should be added to a standard fluoropyrimidine/cisplatin regimen in patients with HER-2 positive tumours. Two and three-drug regimens including 5-FU, cisplatin, with or without an anthracycline, as well as irinotecan or docetaxel-containing regimens are reasonable treatment options for HER-2 negative patients.

Do pseudo-absence selection strategies influence species distribution models and their predictions? An information-theoretic approach based on simulated data

Background Multiple logistic regression is precluded from many practical applications in ecology that aim to predict the geographic distributions of species because it requires absence data, which are rarely available or are unreliable. In order to use multiple logistic regression, many studies have simulated "pseudo-absences" through a number of strategies, but it is unknown how the choice of strategy influences models and their geographic predictions of species. In this paper we evaluate the effect of several prevailing pseudo-absence strategies on the predictions of the geographic distribution of a virtual species whose "true" distribution and relationship to three environmental predictors was predefined. We evaluated the effect of using a) real absences b) pseudo-absences selected randomly from the background and c) two-step approaches: pseudo-absences selected from low suitability areas predicted by either Ecological Niche Factor Analysis: (ENFA) or BIOCLIM. We compared how the choice of pseudo-absence strategy affected model fit, predictive power, and information-theoretic model selection results. Results Models built with true absences had the best predictive power, best discriminatory power, and the "true" model (the one that contained the correct predictors) was supported by the data according to AIC, as expected. Models based on random pseudo-absences had among the lowest fit, but yielded the second highest AUC value (0.97), and the "true" model was also supported by the data. Models based on two-step approaches had intermediate fit, the lowest predictive power, and the "true" model was not supported by the data. Conclusion If ecologists wish to build parsimonious GLM models that will allow them to make robust predictions, a reasonable approach is to use a large number of randomly selected pseudo-absences, and perform model selection based on an information theoretic approach. However, the resulting models can be expected to have limited fit.

Designing business models of cloud platforms

Cloud computing and its three facets (Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS)) are terms that denote new developments in the software industry. In particular, PaaS solutions, also referred to as cloud platforms, are changing the way software is being produced, distributed, consumed, and priced. Software vendors have started considering cloud platforms as a strategic option but are battling to redefine their offerings to embrace PaaS. In contrast to SaaS and IaaS, PaaS allows for value co-creation with partners to develop complementary components and applications. It thus requires multisided business models that bring together two or more distinct customer segments. Understanding how to design PaaS business models to establish a flourishing ecosystem is crucial for software vendors. This doctoral thesis aims to address this issue in three interrelated research parts. First, based on case study research, the thesis provides a deeper understanding of current PaaS business models and their evolution. Second, it analyses and simulates consumers' preferences regarding PaaS business models, using a conjoint approach to find out what determines the choice of cloud platforms. Finally, building on the previous research outcomes, the third part introduces a design theory for the emerging class of PaaS business models, which is grounded on an extensive action design research study with a large European software vendor. Understanding PaaS business models from a market as well as a consumer perspective will, together with the design theory, inform and guide decision makers in their business model innovation plans. It also closes gaps in the research related to PaaS business model design and more generally related to platform business models.

Additive functions in boolean models of gene regulatory network modules.

Gene-on-gene regulations are key components of every living organism. Dynamical abstract models of genetic regulatory networks help explain the genome's evolvability and robustness. These properties can be attributed to the structural topology of the graph formed by genes, as vertices, and regulatory interactions, as edges. Moreover, the actual gene interaction of each gene is believed to play a key role in the stability of the structure. With advances in biology, some effort was deployed to develop update functions in Boolean models that include recent knowledge. We combine real-life gene interaction networks with novel update functions in a Boolean model. We use two sub-networks of biological organisms, the yeast cell-cycle and the mouse embryonic stem cell, as topological support for our system. On these structures, we substitute the original random update functions by a novel threshold-based dynamic function in which the promoting and repressing effect of each interaction is considered. We use a third real-life regulatory network, along with its inferred Boolean update functions to validate the proposed update function. Results of this validation hint to increased biological plausibility of the threshold-based function. To investigate the dynamical behavior of this new model, we visualized the phase transition between order and chaos into the critical regime using Derrida plots. We complement the qualitative nature of Derrida plots with an alternative measure, the criticality distance, that also allows to discriminate between regimes in a quantitative way. Simulation on both real-life genetic regulatory networks show that there exists a set of parameters that allows the systems to operate in the critical region. This new model includes experimentally derived biological information and recent discoveries, which makes it potentially useful to guide experimental research. The update function confers additional realism to the model, while reducing the complexity and solution space, thus making it easier to investigate.

Combination of trastuzumab and letrozole after resistance to sequential trastuzumab and aromatase inhibitor monotherapies in patients with estrogen receptor-positive, HER-2-positive advanced breast cancer: a proof-of-concept trial (SAKK 23/03).

A sequential treatment design was chosen in this trial to ensure complete resistance to single-agent non-steroidal aromatase inhibitor (AI) and trastuzumab both given as monotherapy before receiving the combination of a non-steroidal AI and trastuzumab. Key eligibility criteria included postmenopausal patients with advanced, measurable, human epidermal growth factor receptor-2 (HER-2)-positive disease (assessed by FISH, ratio (≥2)), hormone receptor (HR)-positive disease, and progression on prior treatment with a non-steroidal AI, e.g. letrozole or anastrozole, either in the adjuvant or in the advanced setting. Patients received standard dose trastuzumab monotherapy in step 1 and upon disease progression continued trastuzumab in combination with letrozole in step 2. The primary endpoint was clinical benefit rate (CBR) in step 2. Totally, 13 patients were enrolled. In step 1, six patients (46%) achieved CBR. Median time to progression (TTP) was 161 days (95% confidence interval (CI): 82-281). In step 2, CBR was observed in eight out of the 11 evaluable patients (73%), including one patient with partial response. Median TTP for all the 11 patients was 188 days (95% CI: 77-not reached). Results of this proof-of-concept trial suggest that complete resistance to both AI and trastuzumab can be overcome in a proportion of patients by combined treatment of AI and trastuzumab, as all patients served as their own control. Our results appear promising for a new treatment strategy that offers a chemotherapy-free option for at least a subset of patients with HR-positive, HER-2-positive breast cancer over a clinically relevant time period.