495 research outputs found
Outcomes of preexisting diabetes mellitus in breast, colorectal, and prostate cancer.
This is the author accepted manuscript. The final version is available from Springer Verlag via the DOI in this record.PURPOSE: Preexisting diabetes is associated with increased morbidity and mortality in cancer. We examined the impact of incident cancer on the long-term outcomes of diabetes. METHODS: Using the United Kingdom Clinical Practice Research Datalink, we identified three cohorts of diabetes patients subsequently diagnosed with breast, colorectal, or prostate cancer, each matched to diabetic noncancer controls. Patients were required to have survived at least 1 year after cancer diagnosis (cases) or a matched index date (controls), and were followed up to 10 years for incident microvascular and macrovascular complications and mortality. Multivariate competing risks regression analyses were used to compare outcomes between cancer patients and controls. RESULTS: Overall, there were 3382 cancer patients and 11,135 controls with 59,431 person-years of follow-up. In adjusted analyses, there were no statistically significant (p ≤ 0.05) differences in diabetes complication rates between cancer patients and their controls in any of the three cancer cohorts. Combined, cancer patients were less likely (adjusted hazard ratio [HR] 0.88; 95% CI = 0.79-0.98) to develop retinopathy. Cancer patients were more likely to die of any cause (including cancer), but prostate cancer patients were less likely to die of causes associated with diabetes (HR 0.61; 95% CI = 0.43-0.88). CONCLUSIONS AND IMPLICATIONS: There is no evidence that incident cancer had an adverse impact on the long-term outcomes of preexisting diabetes. IMPLICATIONS FOR CANCER SURVIVORS: These findings are important for cancer survivors with preexisting diabetes because they suggest that substantial improvements in the relative survival of several of the most common types of cancer are not undermined by excess diabetes morbidity and mortality.This study was funded by the Population Research Committee, Cancer Research UK. Quality and Outcomes of Care for Chronic Conditions in Older Patients Diagnosed with Breast, Colorectal, or Prostate Cancer Compared to Non-Cancer Controls: An Observational Study Using the Clinical Practice Research Datalink (CPRD). Reference # 16609. 1 July 2013–29 February, 2016. In addition, Dr. Keating is supported by K24CA181510 from the US National Cancer Institute
Outcomes of preexisting diabetes mellitus in breast, colorectal, and prostate cancer.
This is the author accepted manuscript. The final version is available from Springer Verlag via the DOI in this record.PURPOSE: Preexisting diabetes is associated with increased morbidity and mortality in cancer. We examined the impact of incident cancer on the long-term outcomes of diabetes. METHODS: Using the United Kingdom Clinical Practice Research Datalink, we identified three cohorts of diabetes patients subsequently diagnosed with breast, colorectal, or prostate cancer, each matched to diabetic noncancer controls. Patients were required to have survived at least 1 year after cancer diagnosis (cases) or a matched index date (controls), and were followed up to 10 years for incident microvascular and macrovascular complications and mortality. Multivariate competing risks regression analyses were used to compare outcomes between cancer patients and controls. RESULTS: Overall, there were 3382 cancer patients and 11,135 controls with 59,431 person-years of follow-up. In adjusted analyses, there were no statistically significant (p ≤ 0.05) differences in diabetes complication rates between cancer patients and their controls in any of the three cancer cohorts. Combined, cancer patients were less likely (adjusted hazard ratio [HR] 0.88; 95% CI = 0.79-0.98) to develop retinopathy. Cancer patients were more likely to die of any cause (including cancer), but prostate cancer patients were less likely to die of causes associated with diabetes (HR 0.61; 95% CI = 0.43-0.88). CONCLUSIONS AND IMPLICATIONS: There is no evidence that incident cancer had an adverse impact on the long-term outcomes of preexisting diabetes. IMPLICATIONS FOR CANCER SURVIVORS: These findings are important for cancer survivors with preexisting diabetes because they suggest that substantial improvements in the relative survival of several of the most common types of cancer are not undermined by excess diabetes morbidity and mortality.This study was funded by the Population Research Committee, Cancer Research UK. Quality and Outcomes of Care for Chronic Conditions in Older Patients Diagnosed with Breast, Colorectal, or Prostate Cancer Compared to Non-Cancer Controls: An Observational Study Using the Clinical Practice Research Datalink (CPRD). Reference # 16609. 1 July 2013–29 February, 2016. In addition, Dr. Keating is supported by K24CA181510 from the US National Cancer Institute
Quality of diabetes care in breast, colorectal, and prostate cancer
This is the final version. Available on open access from Springer via the DOI in this recordPURPOSE: Overlooking other medical conditions during cancer treatment and follow-up could result in excess morbidity and mortality, thereby undermining gains associated with early detection and improved treatment of cancer. We compared the quality of care for diabetes patients subsequently diagnosed with breast, colorectal, or prostate cancer to matched, diabetic non-cancer controls. METHODS: Longitudinal cohort study using primary care records from the Clinical Practice Research Datalink, United Kingdom. Patients with pre-existing diabetes were followed for up to 5 years after cancer diagnosis, or after an assigned index date (non-cancer controls). Quality of diabetes care was estimated based on Quality and Outcomes Framework indicators. Mixed effects logistic regression analyses were used to compare the unadjusted and adjusted odds of meeting quality measures between cancer patients and controls, overall and stratified by type of cancer. RESULTS: 3382 cancer patients and 11,135 controls contributed 44,507 person-years of follow-up. In adjusted analyses, cancer patients were less likely to meet five of 14 quality measures, including: total cholesterol ≤ 5 mmol/L (odds ratio [OR] = 0.82; 95% confidence interval [CI], 0.75-0.90); glycosylated hemoglobin ≤ 59 mmol/mol (adjusted OR = 0.77; 95% CI, 0.70-0.85); and albumin creatinine ratio testing (adjusted OR = 0.83; 95% CI, 0.75-0.91). However, cancer patients were as likely as their matched controls to meet quality measures for other diabetes services, including retinal screening, foot examination, and dietary review. CONCLUSIONS: Although in the short-term, cancer patients were less likely to achieve target thresholds for cholesterol and HbA1c, they continued to receive high-quality diabetes primary care throughout 5 years post diagnosis. IMPLICATIONS FOR CANCER SURVIVORS: These findings are important for cancer survivors with pre-existing diabetes because they indicate that high-quality diabetes care is maintained throughout the continuum of cancer diagnosis, treatment, and follow-up.This study was funded by the Population Research Committee, Cancer Research UK. Quality and Outcomes of Care for Chronic Conditions in Older Patients Diagnosed with Breast, Colorectal, or Prostate Cancer Compared to Non-Cancer Controls: An Observational Study Using the Clinical Practice Research Datalink (CPRD). Reference # 16609. 1 July 2013–29 February, 2016. In addition, Dr. Keating is supported by K24CA181510 from the US National Cancer Institute
Anatomy of quantum chaotic eigenstates
The eigenfunctions of quantized chaotic systems cannot be described by
explicit formulas, even approximate ones. This survey summarizes (selected)
analytical approaches used to describe these eigenstates, in the semiclassical
limit. The levels of description are macroscopic (one wants to understand the
quantum averages of smooth observables), and microscopic (one wants
informations on maxima of eigenfunctions, "scars" of periodic orbits, structure
of the nodal sets and domains, local correlations), and often focusses on
statistical results. Various models of "random wavefunctions" have been
introduced to understand these statistical properties, with usually good
agreement with the numerical data. We also discuss some specific systems (like
arithmetic ones) which depart from these random models.Comment: Corrected typos, added a few references and updated some result
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Glycaemic control in people with type 2 diabetes mellitus during and after cancer treatment: A systematic review and meta-analysis
Background
Cancer and Diabetes Mellitus (DM) are leading causes of death worldwide and the prevalence of both is escalating. People with co-morbid cancer and DM have increased morbidity and premature mortality compared with cancer patients with no DM. The reasons for this are likely to be multifaceted but will include the impact of hypo/hyperglycaemia and diabetes therapies on cancer treatment and disease progression. A useful step toward addressing this disparity in treatment outcomes is to establish the impact of cancer treatment on diabetes control.
Aim
The aim of this review is to identify and analyse current evidence reporting glycaemic control (HbA1c) during and after cancer treatment.
Methods
Systematic searches of published quantitative research relating to comorbid cancer and type 2 diabetes mellitus were conducted using databases, including Medline, Embase, PsychINFO, CINAHL and Web of Science (February 2017). Full text publications were eligible for inclusion if they: were quantitative, published in English language, investigated the effects of cancer treatment on glycaemic control, reported HbA1c (%/mmols/mol) and included adult populations with diabetes. Means, standard deviations and sample sizes were extracted from each paper; missing standard deviations were imputed. The completed datasets were analysed using a random effects model. A mixed-effects analysis was undertaken to calculate mean HbA1c (%/mmols/mol) change over three time periods compared to baseline.
Results
The available literature exploring glycaemic control post-diagnosis was mixed. There was increased risk of poor glycaemic control during this time if studies of surgical treatment for gastric cancer are excluded, with significant differences between baseline and 12 months (p < 0.001) and baseline and 24 months (p = 0.002).
Conclusion
We found some evidence to support the contention that glycaemic control during and/or after non-surgical cancer treatment is worsened, and the reasons are not well defined in individual studies. Future studies should consider the reasons why this is the case
How to limit the burden of data collection for Quality Indicators based on medical records? The COMPAQH experience
Information exchange networks for chronic illness care in primary care practices: an observational study
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88018.pdf (publisher's version ) (Open Access)BACKGROUND: Information exchange networks for chronic illness care may influence the uptake of innovations in patient care. Valid and feasible methods are needed to document and analyse information exchange networks in healthcare settings. This observational study aimed to examine the usefulness of methods to study information exchange networks in primary care practices, related to chronic heart failure, diabetes and chronic obstructive pulmonary disease. METHODS: The study was linked to a quality improvement project in the Netherlands. All health professionals in the practices were asked to complete a short questionnaire that documented their information exchange relations. Feasibility was determined in terms of response rates and reliability in terms of reciprocity of reports of receiving and providing information. For each practice, a number of network characteristics were derived for each of the chronic conditions. RESULTS: Ten of the 21 practices in the quality improvement project agreed to participate in this network study. The response rates were high in all but one of the participating practices. For the analysis, we used data from 67 health professionals from eight practices. The agreement between receiving and providing information was, on average, 65.6%. The values for density, centralization, hierarchy, and overlap of the information exchange networks showed substantial variation between the practices as well as between the chronic conditions. The most central individual in the information exchange network could be a nurse or a physician. CONCLUSIONS: Further research is needed to refine the measure of information networks and to test the impact of network characteristics on the uptake of innovations
Can prophylactic breast irradiation contribute to cardiac toxicity in patients with prostate cancer receiving androgen suppressing drugs?
<p>Abstract</p> <p>Background</p> <p>Androgen suppression treatment (AST) might increase the risk of cardiac morbidity in prostate cancer patients. Possible explanations were provided, however, they disregard the potential contribution of prophylactic radiotherapy to the mamillary regions (PMRT, prescribed to avoid gynecomastia).</p> <p>Methods</p> <p>We studied the exposure of the heart in a typical electron beam PMRT setting by evaluating computed tomography (CT) scans in 40 non-cancer patients (age 65 and 75 years in 50% each) and 17 prostate cancer patients. Five of the younger, 7 of the older and 4 of the cancer patients had significant cardiac disease.</p> <p>Results</p> <p>The median distance between skin and outer heart contour decreased with age. In all three groups, patients with cardiac morbidity had smaller distances. When using the CT-determined PMRT beam energy, 10% of the younger, 15% of the older and none of the prostate cancer patients would receive approximately 50% of the prescription dose to a part of the heart (2 had no history of cardiac disease). When using the clinically rather than CT-determined beam energy, as often done in daily practice, an additional 12.5% of the non-cancer and 12% of the prostate cancer patients would be exposed to comparably high doses.</p> <p>Conclusion</p> <p>The present data provide preliminary evidence that PMRT might be a factor that contributes to cardiac side effects. Previous studies that established a relationship between AST and cardiac morbidity did not include information on delivery of PMRT.</p
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