Association of response endpoints with survival outcomes in multiple myeloma

Since the introduction of the proteasome inhibitor bortezomib and the immunomodulatory drugs (IMiDs) thalidomide and lenalidomide, more patients with multiple myeloma are achieving deep, durable responses and disease control, and are living longer. These improvements have afforded more robust analyses of the relationship between response and survival. Generally, these studies have demonstrated that improvements in the quality of response across all stages of treatment are associated with better disease control and longer survival. Thus, achievement of maximal response should be strongly considered, particularly in the frontline setting, but must also be balanced with tolerability, quality of life and patient preferences. In select patients, achievement of a lesser response may be adequate to prolong survival, and attempts to treat these patients to a deeper response may place them at unnecessary risk without significant benefit. Maintenance therapy has been shown to improve the quality of response and disease control and, in some studies, survival. Studies support maintenance therapy for high-risk patients as a standard of care, and there are emerging data supporting maintenance therapy in standard-risk patients to improve progression-free and possibly overall survival. Multidrug regimens combining a proteasome inhibitor and an IMiD have shown exceptional response outcomes with acceptable increases in toxicity in both the frontline and salvage settings, and are becoming a standard treatment approach. Moving forward, the use of immunophenotypic and molecular response criteria will be essential in better understanding the impact of highly active and continuous treatment regimens across myeloma patient populations. Future translational studies will help to develop antimyeloma agents to their fullest potential. The introduction of novel targeted therapies, including the IMiD pomalidomide and the proteasome inhibitors carfilzomib and ixazomib (MLN9708), will provide greater options to individualize treatment and help patients achieve a clinically meaningful response

Comparison Of The Performance Of Several Data Mining Methods For Bad Debt Recovery In The Healthcare Industry

The healthcare industry, specifically hospitals and clinical organizations, are often plagued by unpaid bills and collection agency fees. These unpaid bills contribute significantly to the rising cost of healthcare. Unlike financial institutions, health care providers typically do not collect financial information about their patients.  This lack of information makes it difficult to evaluate whether a particular patient-debtor is likely to pay his/her bill.  In recent years, the industry has started to apply data mining tools to reduce bad-debt balance. This paper compares the effectiveness of five such tools - neural networks, decision trees, logistic regression, memory-based reasoning, and the ensemble model in evaluating whether a debt is likely to be repaid. The data analysis and evaluation of the performance of the models are based on a fairly large unbalanced data sample provided by a healthcare company, in which cases with recovered bad debts are underrepresented. Computer simulation shows that the neural network, logistic regression, and the combined model produced the best classification accuracy. More thorough interpretation of the results is obtained by analyzing the lift and receiver operating characteristic charts. We used the models to score all “unknown” cases, which were not pursued by a company. The best model classified about 34.8% of these cases into “good” cases. To collect bad debts more effectively, we recommend that a company first deploy and use the models, before it refers unrecovered cases to a collection agency.   &nbsp

Mentoring, Career Plateau Tendencies, Turnover Intentions And Implications For Narrowing Pay And Position Gaps Due To Gender Structural Equations Modeling

This study analyzed responses to career-related questions from a survey of experienced Canadian Certified Management Accountants (CMAs), relative experts in the field of management accounting, to address how mentoring affects turnover intentions and career plateau tendency of male and female accounting professionals in industry. In this regard, we used structural equations modeling to build and test a framework illustrating the impact of mentoring and career-related factors. Results indicate that fostering a mentoring environment within an organization can strengthen CMAs perceptions of their careers and employers. Mentoring has also been suggested to enhance womens opportunities to advance in organizations and help women break the glass ceiling. Analyses of data relating to compensation in 2007 and 2009 for a sample of female and male CEOs and operating performance of companies led by these CEOs for these years indicate that, that compensation gaps due to gender appear to be narrowing at the top management level

Mentoring, Career Plateau Tendencies, Turnover Intentions And Implications For Narrowing Pay And Position Gaps Due To Gender Structural Equations Modeling

This study analyzed responses to career-related questions from a survey of experienced Canadian Certified Management Accountants (CMAs), relative experts in the field of management accounting, to address how mentoring affects turnover intentions and career plateau tendency of male and female accounting professionals in industry. In this regard, we used structural equations modeling to build and test a framework illustrating the impact of mentoring and career-related factors. Results indicate that fostering a mentoring environment within an organization can strengthen CMAs perceptions of their careers and employers. Mentoring has also been suggested to enhance womens opportunities to advance in organizations and help women break the glass ceiling. Analyses of data relating to compensation in 2007 and 2009 for a sample of female and male CEOs and operating performance of companies led by these CEOs for these years indicate that, that compensation gaps due to gender appear to be narrowing at the top management level

Clinical Implications of Complex Pharmacokinetics for Daratumumab Dose Regimen in Patients With Relapsed/Refractory Multiple Myeloma

New therapeutic strategies are urgently needed to improve clinical outcomes in patients with multiple myeloma (MM). Daratumumab is a first‐in‐class, CD38 human immunoglobulin G1κ monoclonal antibody approved for treatment of relapsed or refractory MM. Identification of an appropriate dose regimen for daratumumab is challenging due to its target‐mediated drug disposition, leading to time‐ and concentration‐dependent pharmacokinetics. We describe a thorough evaluation of the recommended dose regimen for daratumumab in patients with relapsed or refractory MM