Treatment Of Nonresponse Research Articles

Migraine Preventive Treatment Failure: A Cross-Sectional Study in a Tertiary Center in Brazil

BackgroundIn Brazil, there is a scarcity of evidence on migraine burden in patients who have experienced previous preventive treatment failure (PPTF). ObjectiveTo evaluate the associations between ≥ 3 PPTF and clinical, psychiatric, and medical history data.MethodsIn a retrospective, cross-sectional study, the medical records of migraine patients who first visited a tertiary specialized clinic were examined. We selected adults of both sexes aged ≥ 18 who attended their first appointment between March and July 2017. Ordinal logistic regression models estimated the associations between number of PPTF (no previous treatment, 1 PPTF, 2, and ≥ 3 PPTF) and chronic migraine, the number of diagnosis exams performed, abortive drugs classes used, and non-pharmacological treatments tried (all categorized as none, 1- 3, and ≥ 4), and severe depression (PHQ-9 ≥ 15) and anxiety (GAD-7 ≥ 15), adjusted for sex, age, and years with disease.ResultsData from 440 patients (72.1 % female) with a mean (SD) age of 37.3 (13.0) years were analyzed. The frequency of no previous treatment was 37.7 % (166/440), while 31.8 % (140/440) showed ≥ 3 PPTF. In patients with ≥ 3 PPTF, 35.7 % (50/140) had episodic, and 64.3 % (90/140) had chronic migraine. Compared to no previous treatment, patients with ≥ 3 PPTF showed higher odds (95 % confidence interval) for chronic migraine [2.10 (1.47, 2.98)], ≥ 4 diagnosis exams [6.59 (3.38, 12.84)], ≥ 4 abortive drug classes [16.03 (9.53, 26.94)], ≥ 4 non-pharmacological treatments [5.91 (3.07,11.35)], and severe depression [1.75 (1.07, 2.88)] and anxiety [1.73 (1.05, 2.85)]. ConclusionPatients first visiting a headache specialist had a high frequency of non-response treatment associated with higher migraine burden in terms of chronification, psychiatric comorbidity, acute medication and non-pharmacological treatment inefficacy, and unnecessary exams.

Rare primary pulmonary mucosa-associated lymphoid tissue lymphoma misdiagnosed with tuberculosis: A case report.

Primary pulmonary mucosa-associated lymphoid tissue lymphoma (MALToma) is a rare subtype of non-Hodgkin lymphoma with a relatively low incidence rate clinically. Atypical clinical symptoms and nonspecific chest computed tomography features of the disease make it difficult to determine and treatment is delayed. We discuss the diagnosis and treatment of a patient with primary pulmonary MALToma to raise clinicians' awareness of this condition. A 66-year-old male patient with a medical history of tuberculosis has been experiencing progressive exacerbation of respiratory symptoms and nonresponsive treatment without an unclear diagnosis for 5 years. He was transferred to our hospital because a nonspecific soft tissue mass in the right upper lobe of the lung was found on his chest computed tomography. Laboratory results with serum immunofixation electrophoresis showed polyclonal immunoglobulin (Ig) G, IgM, IgA, and λ-light chain on admission. Pathological examination and immunohistochemical staining of lung biopsy revealed a definitive diagnosis of pulmonary MALToma with stage IV. The patient received immunotherapy with anti-CD20 monoclonal antibody (rituximab), and showed significant clinical improvement at the 6-month follow-up. Diagnosis of primary pulmonary MALToma mainly relies on histopathological examination, and comprehensive laboratory examinations are also necessary. Clinicians should combine laboratory tests (such as immunofixation electrophoresis in our case) to assist in medical diagnosis in cases of atypical clinical manifestations and imaging characteristics. Immunotherapy appears to be the main treatment protocol for advanced patients.

A sampling strategy for assessing habitat coverage at a broad spatial scale

• We develop an adaptive monitoring approach, to estimate the coverage of habitat types using a two-phase sampling scheme. • The adaptive monitoring approach demonstrated high reliability in a simulation study performed on the whole country of Italy. • The method is cost effective, adaptable across habitat types, and transferable to other countries or whole European Union. The quantitative assessment of habitat conservation status is a major task for European Union member states in compliance with Council Directive 92/43. One goal of the European 2030 Biodiversity Strategy is the effective management of habitats that show declining trends. While various approaches have been adopted for national assessments, there is no consensus on how to achieve common statistically sound estimates of the criteria indicated by the EU Directive for the evaluation of the status and trend of habitat types. Here, we present an adaptive monitoring approach based on a two-phase sampling scheme to estimate the coverage of EU terrestrial habitat types, which is one of the four criteria indicated by the Habitats Directive. We used 9 habitats distributed among different EU member states choosing Italy as a case study. The development of the methodological approach is described, and a simulation study was performed to check the precision of the coverage estimators accounting for the lack of sampled data (nonresponse treatment), subregions and sustainable sampling effort. We found that our two-phase sampling approach has the potential to increase precision in estimating the coverage of habitat types (approximated at 1 ha cell size) with respect to the precision achieved by simple random sampling without replacement, which is the simplest sampling approach. Adopting a small sampling fraction ( ⩽ 0.04 % ) of the survey area, the relative standard errors ranged from 7 to 15 % for common habitats whose presence is strongly correlated with the habitat suitability scores furnished by an expert team. In the challenging context of a “mandated” monitoring type, our approach provides sound statistical estimates of habitat coverage with the possibility of applying a standardised and transferable sampling scheme that is easily repeatable over time.

Uncovering the Roles of MicroRNAs in Major Depressive Disorder: From Candidate Diagnostic Biomarkers to Treatment Response Indicators.

Major depressive disorder (MDD) is a recurrent debilitating illness that represents a major health burden due to its increasing worldwide prevalence, unclear pathological mechanism, nonresponsive treatment, and lack of reliable and specific diagnostic biomarkers. Recently, microRNA species (miRs) have gained particular interest because they have the ability to post-transcriptionally regulate gene expression by modulating mRNA stability and translation in a cohesive fashion. By regulating entire genetic circuitries, miRs have been shown to have dysregulated expression levels in blood samples from MDD patients, when compared to healthy subjects. In addition, antidepressant treatment (AD) also appears to alter the expression pattern of several miRs. Therefore, we critically and systematically reviewed herein the studies assessing the potential biomarker role of several candidate miRs for MDD, as well as treatment response monitoring indicators, in order to enrich the current knowledge and facilitate possible diagnostic biomarker development for MDD, which could aid in reducing both patients’ burden and open novel avenues toward a better understanding of MDD neurobiology.

Targeting Key Survey Variables at the Unit Nonresponse Treatment Stage

Abstract In the presence of nonresponse, unadjusted estimators are vulnerable to nonresponse bias when the characteristics of the respondents differ from those of the nonrespondents. To reduce the bias, it is common practice to postulate a nonresponse model linking the response indicators and a set of fully observed variables. Estimated response probabilities are obtained by fitting the selected model, which are then used to adjust the base weights. The resulting estimator, referred to as the propensity score-adjusted estimator, is consistent provided the nonresponse model is correctly specified. In this article, we propose a weighting procedure that may improve the efficiency of propensity score estimators for survey variables identified as key variables by making a more extensive use of the auxiliary information available at the nonresponse treatment stage. Results from a simulation study suggest that the proposed procedure performs well in terms of efficiency when the data are missing at random and also achieves an efficient bias reduction when the data are not missing at random. We further apply our proposed methods to 2017–2018 National Health Nutrition and Examination Survey.

A Comparison Study of Tie Non-response Treatments in Social Networks Analysis.

Analysis of social network data often faces the problem of tie non-response. Recent studies show that the results of social network analyses can be severely biased if tie non-response was ignored. To overcome the problems created by tie non-response, several treatments were proposed in the literature: complete-case approach, unconditional mean imputation, reconstruction, and multiple imputation. In this paper we assessed the impact of tie non-response on social network analysis and investigated the performance of four treatments to handle tie non-response. The simulation results showed that ignoring tie non-response data in network analysis could underestimate the degree and centralization of social networks depending on the types of network and the proportion of missing ties. We also found that unconditional mean imputation was the best tie non-response treatment. Multiple imputation could successfully correct for tie non-response in a few specific situations. Complete case approach and reconstruction, however, were not recommended. We advocate the importance of further research to better understand consequences of tie non-response in social networks analysis and to provide statistical guidance to researchers to tackle this problem in the field.

Inpatient schema therapy for nonresponsive patients with personality pathology: Changes in symptomatic distress, schemas, schema modes, coping styles, experienced parenting styles, and mental well-being.

This study provides an evaluation of group schema therapy (ST) for inpatient treatment of patients with personality pathology who did not respond to previous psychotherapeutic interventions. Forty-two patients were assessed pre- and posttreatment, and 35 patients were evaluated at follow-up 6 months later. The results showed a dropout rate of 35%. Those who dropped out did not differ from those who completed treatment with regard to demographic and clinical variables; the only exception was that those who dropped out showed a lower prevalence of mood disorders. Furthermore, intention-to-treat analyses showed a significant improvement in maladaptive schemas, schema modes, maladaptive coping styles, mental well-being, and psychological distress after treatment, and these improvements were maintained at follow-up. On the other hand, there was no significant change in experienced parenting style as self-reported by patients. Changes in schemas and schema modes measured from pre- to posttreatment were predictive of general psychological distress at follow-up. Overall, these preliminary findings suggest that positive treatment results can be obtained with group ST-based inpatient treatment for patients who did not respond to previous psychotherapeutic interventions. Moreover, these findings are comparable with treatment results for patients without such a nonresponsive treatment history. (PsycINFO Database Record

Calibration for nonresponse treatment: In one or two stepsf

This paper explores the different ways in which auxiliary information can be put to use in calibrated weighting adjustment under survey nonresponse. Information is often present at two levels, the ...

Treatment of non-response in successive sampling

Estimators of the population mean have been presented for sampling on two successive occasions when there is non-response in the sample. These estimators have been derived using the Hansen and Hurwitz (1946) procedure for treating non-response. The estimators were found to be more efficient than the Hansen-Hurwitz estimator.

Pitfalls of the Current Experience Rating Plan: Reply

The essential concerns of Gillam regarding our article seem to be two-fold: First, the National Council on Compensation Insurance (NCCI) has been addressing elements of the nature discussed in the article and is incorporating ongoing improvements to the plan on an evolutionary basis. Second, schedule rating, underwriting selection, and competitive rating plans may be viable supplements to adjust for any continuing inadequacies of the experience rating plan. With respect to the first concern, we applaud the NCCI's responsiveness to needed changes. Some of the problems outlined in our article have been alleviated to varying extents by ongoing improvements to the plan. It would be extremely beneficial if all rating organizations were committed to quick and appropriate response to inequities within any rating plan. To the extent that the NCCI is so committed on an ongoing basis, it could serve as a model to other such organizations. We would, however, point out that the problems identified within the article were not hypothetical examples but real-world. Each of the companies (from which the examples were derived) suffered what was believed to be an inequity resulting from nonresponsive treatment under the experience rating plan. With respect to the second concern, we do not agree with Gillam's suggestion that inadequacies in the experience rating plan can necessarily be corrected through schedule rating, underwriting selection, and competitive rating plans. It is our belief that schedule credits and debits are not actuarially determined; nor are many company underwriters technically capable of correcting pitfalls of the complex experience rating plan with broad-brush applications of credits or debits. Furthermore, the normal pressure for the use of price competition through credits, dividend plans, deviations, and loss-sensitive rating plans is often sales-driven. Use of these tools by an underwriter under such pressure could prove inappropriate. And, once these pricing adjustments are set in motion on a judgment basis, their use may be perpetuated despite changes in underlying exposure.

Glutathiones-transferase activity of leukemic cells as a prognostic factor for response to chemotherapy in acute leukemias

This paper presents an analysis of glutathione S-transferase (GST) activity of leukemic cells in 30 patients with acute leukemias and its predictive value for therapy. Blast cells were isolated from peripheral blood or bone marrow before induction therapy using Ficoll density gradient. GST activity was measured according to the spectrophotometric assay based on the use of 1-chloro-2,4-dinitrobenzene as a substrate. The results did not show any significant differences between activities of the enzyme within the different leukemia types according to the French-American-British (FAB) classification. The patients who achieved complete remission demonstrated the lowest value of enzyme activity. The highest enzyme activity was observed in those patients who achieved partial remission and the non-responsive patients presented a GST value within the median of these two groups. Two categories of patients were represented within the non-responsive treatment group. One was resistant to the conventional therapy and in the other death was caused by infectious or hemorrhagic complications. The mean GST activity in these two groups of patients differ greatly. These results suggest that low GST activity of leukemic cells could be a favourable prognostic factor whereas high GST values could help to find out the group of patients who should be further analysed prior to induction therapy.

Learning set with intra-problem stimulus variation.

Thirty-six discrimination problems of a new type were presented to teen-age human Ss. Each problem contained four trials, and each trial involved a choice between a constant and varied stimulus. The constant stimulus appeared on all trials within a problem The varied stimulus was different on every trial. There were six experimental groups, representing orthogonal combination of a three-treatment reinforcement variable and a two-treatment response vs nonresponse variable. The reinforcement variable involved the following treatments, listed in ascending order of difficulty: constant stimulus correct on all problems, varied stimulus correct on all problems, constant and varied stimuli correct alternately over problems. The response vs nonresponse variable was applied only to Trial 1, and its effects were evaluated on later trials, which showed that the nonresponse treatment was more difficult.