Long-Term Evaluation of Recurrence after Photodynamic Therapy with Topical Methyl Aminolevulinate for Non-Melanoma Skin Cancer: a Hospital-Based Study

Introduction & Objectives: Several factors may influence the decision to pursue nonsurgical modalities for the treatment of non-melanoma skin cancer. Topical photodynamic therapy (PDT) is a non-invasive alternative treatment reported to have a high efficacy when using standardized protocols in Bowen’s disease (BD), superficial basal cell carcinoma (BCC) and in thin nodular BCC. However, long-term recurrence studies are lacking. The aim of this study was to evaluate the long-term efficacy of PDT with topical methylaminolevulinate (MAL) for the treatment of BD and BCC in a dermato-oncology department. Materials & Methods: All patients with the diagnosis of BD or BCC, treated with MAL-PDT from the years 2004 to 2008, were enrolled. Treatment protocol included two MAL-PDT sessions one week apart repeated at three months when incomplete response, using a red light dose of 37-40 J/cm2 and an exposure time of 8’20’’. Clinical records were retrospectively reviewed, and data regarding age, sex, tumour location, size, treatment outcomes and recurrence were registered. Descriptive analysis was performed using chi square tests, followed by survival analysis with the Kaplan-Meier and Cox regression models. Results: Sixty-eight patients (median age 71.0 years, P25;P75=30;92) with a total of 78 tumours (31 BD, 45 superficial BCC, 2 nodular BCC) and a median tumour size of 5 cm2 were treated. Overall, the median follow-up period was 43.5 months (P25;P75=0;100), and a total recurrence rate of 33.8% was observed (24.4 % for BCC vs. 45.2% for BD). Estimated recurrence rates for BCC and BD were 5.0% vs. 7.4% at 6 months, 23.4% vs. 27.9% at 12 months, and 30.0% vs. 72.4% at 60 months. Both age and diagnosis were independent prognostic factors for recurrence, with significantly higher estimated recurrence rates in patients with BD (p=0.0036) or younger than 58 years old (p=0.039). The risk of recurrence (hazard ratio) was 2.4 times higher in patients with BD compared to superficial BCC (95% CI:1.1-5.3; p=0.033), and 2.8 times higher in patients younger than 58 years old (95% CI:1.2-6.5; p=0.02). Conclusions: In the studied population, estimated recurrence rates are higher than those expected from available literature, possibly due to a longer follow-up period. To the authors’ knowledge there is only one other study with a similar follow-up period, regarding BCC solely. BD, as an in situ squamous cell carcinoma, has a higher tendency to recur than superficial BCC. Despite greater cosmesis, PDT might no be the best treatment option for young patients considering their higher risk of recurrence.

Long term (five-year) survival following radical surgical treatment plus adjuvant chemotherapy (FAM) in advanced gastric cancer: a controlled study

Several drugs and their associations are being used for adjuvant or complementary chemotherapy with the aim of improving results of gastric cancer treatment. The objective of this study was to verify the impact of these drugs on nutrition and on survival rate after radical treatment of 53 patients with gastric cancer in stage III of the TNM classification. A control group including 28 patients who had only undergone radical resection was compared to a group of 25 patients who underwent the same operative technique followed by adjuvant polychemotherapy with FAM (5-fluorouracil, Adriamycin, and mitomycin C). In this latter group, chemotherapy toxicity in relation to hepatic, renal, cardiologic, neurological, hematologic, gastrointestinal, and dermatological functions was also studied. There was no significant difference on admission between both groups in relation to gender, race, macroscopic tumoral type of tumor according to the Borrmann classification, location of the tumor in the stomach, length of the gastric resection, or response to cutaneous tests on delayed sensitivity. Chemotherapy was started on average, 2.3 months following surgical treatment. Clinical and laboratory follow-up of all patients continued for 5 years. The following conclusions were reached: 1) The nutritional status and incidence of gastrointestinal manifestation were similar in both groups; 2) There was no occurrence of cardiac, renal, neurological, or hepatic toxicity or death due to the chemotherapeutic method per se; 3) Dermatological alterations and hematological toxicity occurred exclusively in patients who underwent polychemotherapy; 4) There was no significant difference between the rate and site of tumoral recurrence, the disease-free interval, or the survival rate of both study groups; 5) Therefore, we concluded, after a 5-year follow-up, chemotherapy with the FAM regimen did not increase the survival rate.

Long-term fertilizer field trials: comparison of three mathematical response models

Selostus: Lannoituksen pitkäaikaiset kenttäkokeet: kolmen matemaattisen mallin vertailu

Evaluation of two soil carbon models using two Kenyan long term experimental datasets

RothC and Century are two of the most widely used soil organic matter (SOM) models. However there are few examples of specific parameterisation of these models for environmental conditions in East Africa. The aim of this study was therefore, to evaluate the ability of RothC and the Century to estimate changes in soil organic carbon (SOC) resulting from varying land use/management practices for the climate and soil conditions found in Kenya. The study used climate, soils and crop data from a long term experiment (1976-2001) carried out at The Kabete site at The Kenya National Agricultural Research Laboratories (NARL, located in a semi-humid region) and data from a 13 year experiment carried out in Machang'a (Embu District, located in a semi-arid region). The NARL experiment included various fertiliser (0, 60 and 120 kg of N and P2O5 ha(-1)), farmyard manure (FYM - 5 and 10 t ha(-1)) and plant residue treatments, in a variety of combinations. The Machang'a experiment involved a fertiliser (51 kg N ha(-1)) and a FYM (0, 5 and 10 t ha(-1)) treatment with both monocropping and intercropping. At Kabete both models showed a fair to good fit to measured data, although Century simulations for treatments with high levels of FYM were better than those without. At the Machang'a site with monocrops, both models showed a fair to good fit to measured data for all treatments. However, the fit of both models (especially RothC) to measured data for intercropping treatments at Machang'a was much poorer. Further model development for intercrop systems is recommended. Both models can be useful tools in soil C Predictions, provided time series of measured soil C and crop production data are available for validating model performance against local or regional agricultural crops. (C) 2007 Elsevier B.V. All rights reserved.

Describing long-term trends in precipitation using generalized additive models

With the current concern over climate change, descriptions of how rainfall patterns are changing over time can be useful. Observations of daily rainfall data over the last few decades provide information on these trends. Generalized linear models are typically used to model patterns in the occurrence and intensity of rainfall. These models describe rainfall patterns for an average year but are more limited when describing long-term trends, particularly when these are potentially non-linear. Generalized additive models (GAMS) provide a framework for modelling non-linear relationships by fitting smooth functions to the data. This paper describes how GAMS can extend the flexibility of models to describe seasonal patterns and long-term trends in the occurrence and intensity of daily rainfall using data from Mauritius from 1962 to 2001. Smoothed estimates from the models provide useful graphical descriptions of changing rainfall patterns over the last 40 years at this location. GAMS are particularly helpful when exploring non-linear relationships in the data. Care is needed to ensure the choice of smooth functions is appropriate for the data and modelling objectives. (c) 2008 Elsevier B.V. All rights reserved.

Validation of three new measure-correlate-predict models for the long-term prospection of the wind resource

The estimation of the long-term wind resource at a prospective site based on a relatively short on-site measurement campaign is an indispensable task in the development of a commercial wind farm. The typical industry approach is based on the measure-correlate-predict �MCP� method where a relational model between the site wind velocity data and the data obtained from a suitable reference site is built from concurrent records. In a subsequent step, a long-term prediction for the prospective site is obtained from a combination of the relational model and the historic reference data. In the present paper, a systematic study is presented where three new MCP models, together with two published reference models �a simple linear regression and the variance ratio method�, have been evaluated based on concurrent synthetic wind speed time series for two sites, simulating the prospective and the reference site. The synthetic method has the advantage of generating time series with the desired statistical properties, including Weibull scale and shape factors, required to evaluate the five methods under all plausible conditions. In this work, first a systematic discussion of the statistical fundamentals behind MCP methods is provided and three new models, one based on a nonlinear regression and two �termed kernel methods� derived from the use of conditional probability density functions, are proposed. All models are evaluated by using five metrics under a wide range of values of the correlation coefficient, the Weibull scale, and the Weibull shape factor. Only one of all models, a kernel method based on bivariate Weibull probability functions, is capable of accurately predicting all performance metrics studied.

Incorporating technology buying behaviour into UK-based long term domestic stock energy models to provide improved policy analysis

The UK has a target for an 80% reduction in CO2 emissions by 2050 from a 1990 base. Domestic energy use accounts for around 30% of total emissions. This paper presents a comprehensive review of existing models and modelling techniques and indicates how they might be improved by considering individual buying behaviour. Macro (top-down) and micro (bottom-up) models have been reviewed and analysed. It is found that bottom-up models can project technology diffusion due to their higher resolution. The weakness of existing bottom-up models at capturing individual green technology buying behaviour has been identified. Consequently, Markov chains, neural networks and agent-based modelling are proposed as possible methods to incorporate buying behaviour within a domestic energy forecast model. Among the three methods, agent-based models are found to be the most promising, although a successful agent approach requires large amounts of input data. A prototype agent-based model has been developed and tested, which demonstrates the feasibility of an agent approach. This model shows that an agent-based approach is promising as a means to predict the effectiveness of various policy measures.

On the ability of statistical wind-wave models to capture the variability and long-term trends of the North Atlantic winter wave climate

A dynamical wind-wave climate simulation covering the North Atlantic Ocean and spanning the whole 21st century under the A1B scenario has been compared with a set of statistical projections using atmospheric variables or large scale climate indices as predictors. As a first step, the performance of all statistical models has been evaluated for the present-day climate; namely they have been compared with a dynamical wind-wave hindcast in terms of winter Significant Wave Height (SWH) trends and variance as well as with altimetry data. For the projections, it has been found that statistical models that use wind speed as independent variable predictor are able to capture a larger fraction of the winter SWH inter-annual variability (68% on average) and of the long term changes projected by the dynamical simulation. Conversely, regression models using climate indices, sea level pressure and/or pressure gradient as predictors, account for a smaller SWH variance (from 2.8% to 33%) and do not reproduce the dynamically projected long term trends over the North Atlantic. Investigating the wind-sea and swell components separately, we have found that the combination of two regression models, one for wind-sea waves and another one for the swell component, can improve significantly the wave field projections obtained from single regression models over the North Atlantic.

Forecasting accuracy and estimation uncertainty using VAR models with short- and long-term economic restrictions: a Monte-Carlo study

Using vector autoregressive (VAR) models and Monte-Carlo simulation methods we investigate the potential gains for forecasting accuracy and estimation uncertainty of two commonly used restrictions arising from economic relationships. The Örst reduces parameter space by imposing long-term restrictions on the behavior of economic variables as discussed by the literature on cointegration, and the second reduces parameter space by imposing short-term restrictions as discussed by the literature on serial-correlation common features (SCCF). Our simulations cover three important issues on model building, estimation, and forecasting. First, we examine the performance of standard and modiÖed information criteria in choosing lag length for cointegrated VARs with SCCF restrictions. Second, we provide a comparison of forecasting accuracy of Ötted VARs when only cointegration restrictions are imposed and when cointegration and SCCF restrictions are jointly imposed. Third, we propose a new estimation algorithm where short- and long-term restrictions interact to estimate the cointegrating and the cofeature spaces respectively. We have three basic results. First, ignoring SCCF restrictions has a high cost in terms of model selection, because standard information criteria chooses too frequently inconsistent models, with too small a lag length. Criteria selecting lag and rank simultaneously have a superior performance in this case. Second, this translates into a superior forecasting performance of the restricted VECM over the VECM, with important improvements in forecasting accuracy ñreaching more than 100% in extreme cases. Third, the new algorithm proposed here fares very well in terms of parameter estimation, even when we consider the estimation of long-term parameters, opening up the discussion of joint estimation of short- and long-term parameters in VAR models.

The Conway-Maxwell-Poisson-generalized gamma regression model with long-term survivors

In this paper, we proposed a flexible cure rate survival model by assuming the number of competing causes of the event of interest following the Conway-Maxwell distribution and the time for the event to follow the generalized gamma distribution. This distribution can be used to model survival data when the hazard rate function is increasing, decreasing, bathtub and unimodal-shaped including some distributions commonly used in lifetime analysis as particular cases. Some appropriate matrices are derived in order to evaluate local influence on the estimates of the parameters by considering different perturbations, and some global influence measurements are also investigated. Finally, data set from the medical area is analysed.

Potentially modifiable predictors of mortality in patients treated with long-term oxygen therapy

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Predictors of first-year survival in patients with advanced COPD treated using long-term oxygen therapy

Little evidence-based guidance is available to aid clinicians in determining short-term prognoses in very severe COPD patients. Therefore, the present study was designed to provide a prospective assessment (1) of the mortality rates and (2) whether the baseline measurements may be determinants of 1-year mortality in hypoxemic COPD patients receiving long-term oxygen therapy (LTOT).Seventy-eight clinically stable patients with advanced COPD treated using LTOT were enrolled in a prospective cohort study. Outcome variable: first-year mortality. Baseline measurements: categorical variables: age (<60 or >= 60 years); gender; body mass index (<20 or >= 20 kg/m(2)); fat-free mass (FFM) index (<16 [men] and <15kg/m(2) [women]; baseline dyspnea index (BDI) (<= 3 or >3); and corticosteroid use. Continuous variables: smoking history; lung function; FFM; fat mass; hemoglobin; hematocrit; arterial blood gases; forearm muscle strength; St. George's Respiratory Questionnaire (SGRQ); and comorbidity score. By the end of 1-year of follow-up, 12 patients (15.4%) had died. Kaplan-Meier curves showed that BDI <= 3 was the only variable associated with higher mortality. Cox proportional hazards analysis revealed that tower PaO2 and SPO2, higher PaCO2 and SGRQ scores were associated with reduced survival. In the multivariate analysis, BDI remained predictive of mortality (hazard ratio [HR], 0.50; 95% confidence interval [CI], 0.31-0.81), as did PaO2 (HR, 0.49; 95% CI, 0.26-0.95). These data suggest that readily available parameters as dyspnea intensity and hypoxemia severity may be useful in predicting first-year survival rates in advanced COPD patients receiving LTOT (C) 2007 Elsevier Ltd. All rights reserved.

De Novo Thrombotic Microangiopathy After Kidney Transplantation: Clinical Features, Treatment, and Long-Term Patient and Graft Survival

Introduction. Posttransplant thrombotic microangiopathy (TMA)/hemolytic uremic syndrome (HUS) can occur as a recurrent or de novo disease. Methods. A retrospective single-center observational study was applied in order to examine the incidence and outcomes of de novo TMA/HUS among transplantations performed between 2000 and 2010. Recurrent HUS or antibody-mediated rejections were excluded. Results. Seventeen (1.1%) among 1549 kidney transplant recipients fulfilled criteria for de novo TMA. The mean follow-up was 572 days (range, 69-1769). Maintenance immunosuppression was prednisone, tacrolimus (TAC), and mycophenolic acid in 14 (82%) patients. Mean age at onset was 40 +/- 15 years, and serum creatinine was 6.1 +/- 4.1 mg/dL. TMA occurred at a median of 25 days (range, 1-1755) after transplantation. Nine (53%) patients developed TMA within 1 month of transplantation and only 12% after 1 year. Clinical features were anemia (hemoglobin < 10 g/dL) in 9 (53%) patients, thrombocytopenia in 7 (41%), and increased lactate dehydrogenase in 12 (70%). Decreased haptoglobin was observed in 64% and schistocytes in 35%. Calcineurin inhibitor (CM) withdrawal or reduction was the first step in the management of 10/15 (66%) patients, and 6 (35%) received fresh frozen plasma (FFP) and/or plasmapheresis. TAC was successfully reintroduced in six patients after a median of 17 days. Eight (47%) patients needed dialytic support after TMA diagnosis and 75% remained on dialysis. At 4 years of follow-up, death-censored graft survival was worse for TMA group (43.0% versus 85.6%, log-rank = 0.001; hazard ratio = 3.74) and there was no difference in patient survival (53.1% versus 82.2%, log-rank = 0.24). Conclusion. De novo TMA after kidney transplantation is a rare but severe condition with poor graft outcomes. This syndrome may not be fully manifested, and clinical suspicion is essential for early diagnosis and treatment, based mainly in CM withdrawal and FFP infusions and/or plasmapheresis.

ATG based combination therapy - a novel clinically relevant approach to promote regulation and induce long-term allograft survival

Regulatory T cells (Treg) actively regulate alloimmune responses and promote transplantation tolerance. Polyclonal anti-thymocyte globulin (ATG), a widely used induction therapy in clinical organ transplantation, depletes peripheral T cells. However, resistance to tolerance induction is seen with certain T cell depleting strategies and is attributed to alterations in the balance of naïve, memory and regulatory T cells. Here we report a novel reagent, murine ATG (mATG), depletes T cells but preferentially spares CD25+ natural Tregs which limit skewing of T cell repertoire toward T-effector-memory (Tem) phenotype among the recovering T cells. T-cell depletion with mATG combined with CTLA4Ig and Sirolimus synergize to prolong graft survival by tipping the Treg/Tem balance further in favor of Tregs by preserving Tregs, facilitating generation of new Tregs by a conversion mechanism and limiting Tem expansion in response to alloantigen and homeostatic proliferation. These results provide the rationale for translating such novel combination therapies to promote tolerance in primate and human organ transplantation.