Clinical practice guidelines for the management of cryptococcal disease: 2010 update by the infectious diseases society of america.

Cryptococcosis is a global invasive mycosis associated with significant morbidity and mortality. These guidelines for its management have been built on the previous Infectious Diseases Society of America guidelines from 2000 and include new sections. There is a discussion of the management of cryptococcal meningoencephalitis in 3 risk groups: (1) human immunodeficiency virus (HIV)-infected individuals, (2) organ transplant recipients, and (3) non-HIV-infected and nontransplant hosts. There are specific recommendations for other unique risk populations, such as children, pregnant women, persons in resource-limited environments, and those with Cryptococcus gattii infection. Recommendations for management also include other sites of infection, including strategies for pulmonary cryptococcosis. Emphasis has been placed on potential complications in management of cryptococcal infection, including increased intracranial pressure, immune reconstitution inflammatory syndrome (IRIS), drug resistance, and cryptococcomas. Three key management principles have been articulated: (1) induction therapy for meningoencephalitis using fungicidal regimens, such as a polyene and flucytosine, followed by suppressive regimens using fluconazole; (2) importance of early recognition and treatment of increased intracranial pressure and/or IRIS; and (3) the use of lipid formulations of amphotericin B regimens in patients with renal impairment. Cryptococcosis remains a challenging management issue, with little new drug development or recent definitive studies. However, if the diagnosis is made early, if clinicians adhere to the basic principles of these guidelines, and if the underlying disease is controlled, then cryptococcosis can be managed successfully in the vast majority of patients.

Qualitative analysis of the interdisciplinary interaction between data analysis specialists and novice clinical researchers.

BACKGROUND: The inherent complexity of statistical methods and clinical phenomena compel researchers with diverse domains of expertise to work in interdisciplinary teams, where none of them have a complete knowledge in their counterpart's field. As a result, knowledge exchange may often be characterized by miscommunication leading to misinterpretation, ultimately resulting in errors in research and even clinical practice. Though communication has a central role in interdisciplinary collaboration and since miscommunication can have a negative impact on research processes, to the best of our knowledge, no study has yet explored how data analysis specialists and clinical researchers communicate over time. METHODS/PRINCIPAL FINDINGS: We conducted qualitative analysis of encounters between clinical researchers and data analysis specialists (epidemiologist, clinical epidemiologist, and data mining specialist). These encounters were recorded and systematically analyzed using a grounded theory methodology for extraction of emerging themes, followed by data triangulation and analysis of negative cases for validation. A policy analysis was then performed using a system dynamics methodology looking for potential interventions to improve this process. Four major emerging themes were found. Definitions using lay language were frequently employed as a way to bridge the language gap between the specialties. Thought experiments presented a series of "what if" situations that helped clarify how the method or information from the other field would behave, if exposed to alternative situations, ultimately aiding in explaining their main objective. Metaphors and analogies were used to translate concepts across fields, from the unfamiliar to the familiar. Prolepsis was used to anticipate study outcomes, thus helping specialists understand the current context based on an understanding of their final goal. CONCLUSION/SIGNIFICANCE: The communication between clinical researchers and data analysis specialists presents multiple challenges that can lead to errors.

A strategy to advance the evidence base in palliative medicine: formation of a palliative care research cooperative group.

BACKGROUND: Palliative medicine has made rapid progress in establishing its scientific and clinical legitimacy, yet the evidence base to support clinical practice remains deficient in both the quantity and quality of published studies. Historically, the conduct of research in palliative care populations has been impeded by multiple barriers including health care system fragmentation, small number and size of potential sites for recruitment, vulnerability of the population, perceptions of inappropriateness, ethical concerns, and gate-keeping. METHODS: A group of experienced investigators with backgrounds in palliative care research convened to consider developing a research cooperative group as a mechanism for generating high-quality evidence on prioritized, clinically relevant topics in palliative care. RESULTS: The resulting Palliative Care Research Cooperative (PCRC) agreed on a set of core principles: active, interdisciplinary membership; commitment to shared research purposes; heterogeneity of participating sites; development of research capacity in participating sites; standardization of methodologies, such as consenting and data collection/management; agile response to research requests from government, industry, and investigators; focus on translation; education and training of future palliative care researchers; actionable results that can inform clinical practice and policy. Consensus was achieved on a first collaborative study, a randomized clinical trial of statin discontinuation versus continuation in patients with a prognosis of less than 6 months who are taking statins for primary or secondary prevention. This article describes the formation of the PCRC, highlighting processes and decisions taken to optimize the cooperative group's success.

Variation in use of surveillance colonoscopy among colorectal cancer survivors in the United States.

BACKGROUND: Clinical practice guidelines recommend colonoscopies at regular intervals for colorectal cancer (CRC) survivors. Using data from a large, multi-regional, population-based cohort, we describe the rate of surveillance colonoscopy and its association with geographic, sociodemographic, clinical, and health services characteristics. METHODS: We studied CRC survivors enrolled in the Cancer Care Outcomes Research and Surveillance (CanCORS) study. Eligible survivors were diagnosed between 2003 and 2005, had curative surgery for CRC, and were alive without recurrences 14 months after surgery with curative intent. Data came from patient interviews and medical record abstraction. We used a multivariate logit model to identify predictors of colonoscopy use. RESULTS: Despite guidelines recommending surveillance, only 49% of the 1423 eligible survivors received a colonoscopy within 14 months after surgery. We observed large regional differences (38% to 57%) across regions. Survivors who received screening colonoscopy were more likely to: have colon cancer than rectal cancer (OR = 1.41, 95% CI: 1.05-1.90); have visited a primary care physician (OR = 1.44, 95% CI: 1.14-1.82); and received adjuvant chemotherapy (OR = 1.75, 95% CI: 1.27-2.41). Compared to survivors with no comorbidities, survivors with moderate or severe comorbidities were less likely to receive surveillance colonoscopy (OR = 0.69, 95% CI: 0.49-0.98 and OR = 0.44, 95% CI: 0.29-0.66, respectively). CONCLUSIONS: Despite guidelines, more than half of CRC survivors did not receive surveillance colonoscopy within 14 months of surgery, with substantial variation by site of care. The association of primary care visits and adjuvant chemotherapy use suggests that access to care following surgery affects cancer surveillance.

Facilitators and barriers to hypertension self-management in urban African Americans: perspectives of patients and family members.

INTRODUCTION: We aimed to inform the design of behavioral interventions by identifying patients' and their family members' perceived facilitators and barriers to hypertension self-management. MATERIALS AND METHODS: We conducted focus groups of African American patients with hypertension and their family members to elicit their views about factors influencing patients' hypertension self-management. We recruited African American patients with hypertension (n = 18) and their family members (n = 12) from an urban, community-based clinical practice in Baltimore, Maryland. We conducted four separate 90-minute focus groups among patients with controlled (one group) and uncontrolled (one group) hypertension, as well as their family members (two groups). Trained moderators used open-ended questions to assess participants' perceptions regarding patient, family, clinic, and community-level factors influencing patients' effective hypertension self-management. RESULTS: Patient participants identified several facilitators (including family members' support and positive relationships with doctors) and barriers (including competing health priorities, lack of knowledge about hypertension, and poor access to community resources) that influence their hypertension self-management. Family members also identified several facilitators (including their participation in patients' doctor's visits and discussions with patients' doctors outside of visits) and barriers (including their own limited health knowledge and patients' lack of motivation to sustain hypertension self-management behaviors) that affect their efforts to support patients' hypertension self-management. CONCLUSION: African American patients with hypertension and their family members reported numerous patient, family, clinic, and community-level facilitators and barriers to patients' hypertension self-management. Patients' and their family members' views may help guide efforts to tailor behavioral interventions designed to improve hypertension self-management behaviors and hypertension control in minority populations.

An active learning approach for rapid characterization of endothelial cells in human tumors.

Currently, no available pathological or molecular measures of tumor angiogenesis predict response to antiangiogenic therapies used in clinical practice. Recognizing that tumor endothelial cells (EC) and EC activation and survival signaling are the direct targets of these therapies, we sought to develop an automated platform for quantifying activity of critical signaling pathways and other biological events in EC of patient tumors by histopathology. Computer image analysis of EC in highly heterogeneous human tumors by a statistical classifier trained using examples selected by human experts performed poorly due to subjectivity and selection bias. We hypothesized that the analysis can be optimized by a more active process to aid experts in identifying informative training examples. To test this hypothesis, we incorporated a novel active learning (AL) algorithm into FARSIGHT image analysis software that aids the expert by seeking out informative examples for the operator to label. The resulting FARSIGHT-AL system identified EC with specificity and sensitivity consistently greater than 0.9 and outperformed traditional supervised classification algorithms. The system modeled individual operator preferences and generated reproducible results. Using the results of EC classification, we also quantified proliferation (Ki67) and activity in important signal transduction pathways (MAP kinase, STAT3) in immunostained human clear cell renal cell carcinoma and other tumors. FARSIGHT-AL enables characterization of EC in conventionally preserved human tumors in a more automated process suitable for testing and validating in clinical trials. The results of our study support a unique opportunity for quantifying angiogenesis in a manner that can now be tested for its ability to identify novel predictive and response biomarkers.

Implementation of automated reporting of estimated glomerular filtration rate among Veterans Affairs laboratories: a retrospective study.

BACKGROUND: Automated reporting of estimated glomerular filtration rate (eGFR) is a recent advance in laboratory information technology (IT) that generates a measure of kidney function with chemistry laboratory results to aid early detection of chronic kidney disease (CKD). Because accurate diagnosis of CKD is critical to optimal medical decision-making, several clinical practice guidelines have recommended the use of automated eGFR reporting. Since its introduction, automated eGFR reporting has not been uniformly implemented by U. S. laboratories despite the growing prevalence of CKD. CKD is highly prevalent within the Veterans Health Administration (VHA), and implementation of automated eGFR reporting within this integrated healthcare system has the potential to improve care. In July 2004, the VHA adopted automated eGFR reporting through a system-wide mandate for software implementation by individual VHA laboratories. This study examines the timing of software implementation by individual VHA laboratories and factors associated with implementation. METHODS: We performed a retrospective observational study of laboratories in VHA facilities from July 2004 to September 2009. Using laboratory data, we identified the status of implementation of automated eGFR reporting for each facility and the time to actual implementation from the date the VHA adopted its policy for automated eGFR reporting. Using survey and administrative data, we assessed facility organizational characteristics associated with implementation of automated eGFR reporting via bivariate analyses. RESULTS: Of 104 VHA laboratories, 88% implemented automated eGFR reporting in existing laboratory IT systems by the end of the study period. Time to initial implementation ranged from 0.2 to 4.0 years with a median of 1.8 years. All VHA facilities with on-site dialysis units implemented the eGFR software (52%, p<0.001). Other organizational characteristics were not statistically significant. CONCLUSIONS: The VHA did not have uniform implementation of automated eGFR reporting across its facilities. Facility-level organizational characteristics were not associated with implementation, and this suggests that decisions for implementation of this software are not related to facility-level quality improvement measures. Additional studies on implementation of laboratory IT, such as automated eGFR reporting, could identify factors that are related to more timely implementation and lead to better healthcare delivery.

Evaluating marker-guided treatment selection strategies

© 2014, The International Biometric Society.A potential venue to improve healthcare efficiency is to effectively tailor individualized treatment strategies by incorporating patient level predictor information such as environmental exposure, biological, and genetic marker measurements. Many useful statistical methods for deriving individualized treatment rules (ITR) have become available in recent years. Prior to adopting any ITR in clinical practice, it is crucial to evaluate its value in improving patient outcomes. Existing methods for quantifying such values mainly consider either a single marker or semi-parametric methods that are subject to bias under model misspecification. In this article, we consider a general setting with multiple markers and propose a two-step robust method to derive ITRs and evaluate their values. We also propose procedures for comparing different ITRs, which can be used to quantify the incremental value of new markers in improving treatment selection. While working models are used in step I to approximate optimal ITRs, we add a layer of calibration to guard against model misspecification and further assess the value of the ITR non-parametrically, which ensures the validity of the inference. To account for the sampling variability of the estimated rules and their corresponding values, we propose a resampling procedure to provide valid confidence intervals for the value functions as well as for the incremental value of new markers for treatment selection. Our proposals are examined through extensive simulation studies and illustrated with the data from a clinical trial that studies the effects of two drug combinations on HIV-1 infected patients.