Abstract

BACKGROUND: Prior meta-analyses have yielded conflicting results regarding the outcomes of treatment of stable coronary artery disease (CAD) with initial percutaneous coronary intervention (PCI) vs medical therapy. However, most of the studies in prior systematic reviews used balloon angioplasty as well as medical therapies that do not reflect current interventional or medical practices. We therefore performed a meta-analysis of all randomized clinical trials comparing initial coronary stent implantation with medical therapy to determine the effect on death, nonfatal myocardial infarction (MI), unplanned revascularization, and persistent angina.

METHODS: Prospective randomized trials were identified by searches of the MEDLINE database from 1970 to September 2011. Trials in which stents were used in less than 50% of PCI procedures were excluded. Data were extracted from each study, and summary odds ratios (ORs) were obtained using a random effects model.

RESULTS: Eight trials enrolling 7229 patients were identified. Three trials enrolled stable patients after MI, whereas 5 studies enrolled patients with stable angina and/or ischemia on stress testing. Mean weighted follow-up was 4.3 years. The respective event rates for death with stent implantation and medical therapy were 8.9% and 9.1% (OR, 0.98; 95% CI, 0.84-1.16); for nonfatal MI, 8.9% and 8.1% (OR, 1.12; 95% CI, 0.93-1.34); for unplanned revascularization, 21.4% and 30.7% (OR, 0.78; 95% CI, 0.57-1.06); and for persistent angina, 29% and 33% (OR, 0.80; 95% CI, 0.60-1.05).

CONCLUSION: Initial stent implantation for stable CAD shows no evidence of benefit compared with initial medical therapy for prevention of death, nonfatal MI, unplanned revascularization, or angina.

These results support the practice of continuing metformin in patients with type 2 diabetes who require insulin, rather than switching them to insulin alone.

CONCLUSIONS: Tai chi training appears to reduce balance impairments in patients with mild-to-moderate Parkinson's disease, with additional benefits of improved functional capacity and reduced falls. (Funded by the National Institute of Neurological Disorders and Stroke; ClinicalTrials.gov number, NCT00611481.).

CONCLUSIONS: Tai chi training appears to reduce balance impairments in patients with mild-to-moderate Parkinson's disease, with additional benefits of improved functional capacity and reduced falls. (Funded by the National Institute of Neurological Disorders and Stroke; ClinicalTrials.gov number, NCT00611481.).

Perspective

Performance Improvement in Health Care — Seizing the Moment

David Blumenthal, M.D., M.P.P.

April 25, 2012 (10.1056/NEJMp1203427)

Article

References

We have an unprecedented opportunity to create a high-performance health system in the United States. Recent statutes, including the Affordable Care Act, the American Recovery and Reinvestment Act, and the Health Information Technology for Economic and Clinical Health Act, provide the federal government with important powers for catalyzing improvement in service delivery. These new powers touch all the critical levers for advancing health system performance: payment policy, organization and infrastructure, public health, and essential information for health care decision making. The national performance-improvement toolbox is now well stocked.

But using that toolbox effectively is enormously challenging. Federal budget deficits and rising health care expenditures create pressures to quickly adopt simple expedients, such as cuts in benefits and provider payments. At the same time, the very number and diversity of available forms of authority, each with its own legal quirks and restrictions, creates huge conceptual and logistic complexity.

So how can the federal government seize this moment to improve health system performance? Without close coordination driven by an overriding vision, the dutiful, line-by-line implementation of each individual program will not create the breakthroughs in performance that are needed to make our health system sustainable. The Commonwealth Fund Commission on a High Performance Health System, which I chair, believes that the government needs a comprehensive, disciplined implementation plan for health system improvement that takes full, thoughtful advantage of its new opportunities.1

First, the commission believes, government leadership for performance improvement requires clear goals, beginning with concrete cost-containment and quality-improvement targets. The federal government should aim to reduce the rate of increase in national health expenditures per capita to the annual projected growth of the gross domestic product (GDP) per capita plus 0.5 percentage points by 2016 and to maintain that rate through 2021. Achieving this target would reduce national health care expenditures by $893 billion over 10 years and hold health care spending as a share of the GDP in 2021 to 18.9%, as compared with the current projection of 20.1%. The target for health care quality should be to double the annual rate of improvement on the quality metrics tracked by the Agency for Healthcare Research and Quality, from the current 2.3% to 4.6% by 2016.

The guiding vision should also be based on the understanding that performance improvement requires that clinicians and patients be enabled to make better health care decisions by giving them the best available information when and where they need it and making it easy to do the right thing. Clinicians and patients need information about patients' personal health and health care and about medical evidence relevant to their decisions. Clinicians need environmental supports and financial incentives to choose diagnostic and therapeutic pathways that maximize the value of care. Organizational arrangements must support collaboration, teamwork, and coordination of care.

The federal government can and should facilitate the creation of these conditions, and it should certainly avoid actions that undermine them. But the actual work will fall overwhelmingly to millions of people and institutions in the private and public sectors working together in local communities; they will need to set clear priorities, preferably through a collaborative process that involves states and private-sector entities. For both humane and pragmatic reasons, the federal government should start by focusing its robust new forms of authority on improving care for high-cost patients with multiple chronic conditions. Patients with one or more chronic conditions use 96% of home health visits, 93% of prescriptions, and nearly 80% of physician visits and hospital stays — and these sickest patients account for a disproportionate share of U.S. health care expenditures (see graph

Distribution of Health Care Expenditures for the U.S. Population, According to Magnitude of Expenditure, 2009.).2 Any successful cost-containment effort will have to address their resource utilization. Furthermore, such patients are disproportionately affected by the quality and safety deficits in our health care system and stand to benefit greatly from performance improvements.

The challenge is to find a way to empower providers and patients to rapidly improve the care they offer and receive. Though there is no battle-tested plan for doing so, a logical approach would emphasize three tools and one overall policy strategy.

The tools are improved primary care, payment reform, and better information. Nothing is more important for improving performance in caring for patients with complex conditions than coordinating care and enhancing access during normal office hours, nights, and weekends3 — precisely the role that good primary care plays in high-performing health systems. Payment reform is essential to enabling providers, and perhaps patients, to participate in the savings that result from reductions in costs and improvements in quality.4 One stakeholder's cost is another's revenue or desired service; to support the reduction of unnecessary or marginally useful services, financial incentives must reward rather than punish such behavior, since it affects all payers, providers, and patients, not just Medicare. And care coordination and cost management depend on having accurate, timely, and actionable information in real time at the point of decision making. The availability and effective use of health information technology are therefore essential to improving health system performance for high-cost patients.

So, what policies are needed to get these tools installed and functioning effectively? Since health care systems are local phenomena, their reform must occur locally. The Commission on a High Performance Health System proposes that the federal government work with other stakeholders to launch a nationwide, community-based initiative as soon as possible to improve the care of high-cost patients with multiple chronic conditions. This program should recruit 50 to 100 geographic areas or health improvement communities (HICs), encompassing a substantial segment of the U.S. population (approaching 60%). The definition of “community” will vary — from a city to a county, a hospital-referral region, a neighborhood, or a state — but to be eligible, a community should have a substantial concentration of high-cost patients.

In return for financial and technical support and regulatory accommodations, such as necessary Medicare and Medicaid waivers, participating communities should involve all or most local payers and providers in community-based accountable care arrangements. Recent research suggests that this type of program could save $184 billion, or about 21% of the $893 billion savings target for national health care expenditures.5

Supporting a community-based initiative for high-cost patients would fit within the mandate of the new Center for Medicare and Medicaid Innovation, which has broad authority and $10 billion to undertake new programs to contain Medicare and Medicaid costs while protecting the quality of care. The federal government should also use a range of additional programs and resources to help fundamentally redesign payment, primary care, and information use in participating HICs. HICs should be encouraged to develop innovative gain-sharing payment arrangements that are consistent across public and private payers. Payment redesign should materially improve the revenue, flexibility, and resources available to medical homes in ways that promote and reward the coordination of care by primary care providers for high-cost patients. HICs should be strongly encouraged to have comprehensive health information technology plans for their communities. In all this work, the Center for Medicare and Medicaid Innovation should provide as much flexibility as possible to HICs, respond rapidly to their needs for federal data, and minimize any regulatory and reporting burdens not vital to ensuring cost containment and quality improvement.

For decades, the United States has seemed powerless to curb excessive health care spending and improve the quality of care. Now, the tools for achieving fundamental reform are in place, but using them requires the federal government and its private and public partners to leave business as usual behind and to create and implement a plan that addresses the root causes of our health care crisis. Our commission believes that the establishment of HICs to transform the care of patients with multiple chronic conditions could provide such a plan. Other approaches may be equally sound. But above all else, we must act.

Disclosure forms provided by the author are available with the full text of this article at NEJM.org.

This article (10.1056/NEJMp1203427) was published on April 25, 2012, at NEJM.org.

Source Information

From Harvard Medical School, Boston; and the Commission on a High Performance Health System, Commonwealth Fund, New York.

References

1. 1

   Commission on a High Performance Health System. The performance improvement imperative: utilizing a coordinated, community-based approach to improve care and lower costs for chronically ill patients. New York: The Commonwealth Fund, April 2012.
   

2. 2

   Anderson G. Chronic care: making the case for ongoing care. Princeton, NJ: Robert Wood Johnson Foundation, February 2010.
   

3. 3

   Bodenheimer T, Wagner EH, Grumbach K. Improving primary care for patients with chronic illness. JAMA 2002;288:1775-1779
   CrossRef | Web of Science | Medline

4. 4

   Guterman S, Davis K, Schoen C, Stremikis K. Reforming provider payment: essential building block for health reform. New York: The Commonwealth Fund, March 2009.
   

5. 5

   Holahan J, Schoen C, McMorrow S. The potential savings from enhanced chronic care management policies. Washington, DC: Urban Institute, November 2011.
   

<blockquote class='posterous_medium_quote'>Clinicians should monitor glucose or glycated hemoglobin in patients with multiple risk factors for diabetes who take statins, but they should continue to prescribe statins when indicated as part of a multifactorial approach to managing cardiovascular risk.</blockquote>

<blockquote class='posterous_long_quote'><div class="abstr"><h4>CONCLUSIONS: </h4><p>For subjects in status epilepticus, intramuscular midazolam is at least as safe and effective as intravenous lorazepam for prehospital seizure cessation. (Funded by the National Institute of Neurological Disorders and Stroke and others; ClinicalTrials.gov number, ClinicalTrials.gov NCT00809146.).</p></div><div class="err"><h3>Comment in</h3><ul><li>N Engl J Med. 2012 Feb 16;366(7):659-60.</li></ul></div></blockquote>

For patients is status epilepticus, it is safe and effective to use IM midazolam rather than IV benzos.

<div class='posterous_quote_citation'> Abstract at ncbi.nlm.nih.gov</div>

In a RCT with more than 25,000 people in each arm, once only screening colonoscopy was compared with 2nd annual FOBT over a 10 year period.

The cancer yield was similar (30 vs 33), More advanced adenomas were found in the colonoscopy group. Patients preferred FOBT and were more likely to participate.

Arch Intern Med. 2012 Jan 23;172(2):101-11.

Effect of exercise training on depressive symptoms among patients with a chronic illness: a systematic review and meta-analysis of randomized controlled trials.

Herring MP, Puetz TW, O'Connor PJ, Dishman RK.

Source

Department of Epidemiology, University of Alabama, Birmingham, AL 35294, USA. mattpherring@gmail.com

Abstract

BACKGROUND:

Physical inactivity and comorbid depressive symptoms are prevalent among patients with a chronic illness. To our knowledge, randomized controlled trials of the effects of exercise training on depressive symptoms among patients with a chronic illness have not been systematically reviewed. We estimated the population effect of exercise training on depressive symptoms and determined whether the effect varied according to patient characteristics and modifiable features of exercise exposure and clinical settings.

METHODS:

Articles published before June 1, 2011, were located using the Physical Activity Guidelines for Americans Scientific Database, Google Scholar, MEDLINE, PsycINFO, PubMed, and Web of Science. Ninety articles involving 10,534 sedentary patients with a chronic illness were selected. Included articles required (1) randomized allocation to an exercise intervention or nonexercise comparison condition and (2) a depression outcome assessed at baseline and at mid- and/or postintervention. Hedges d effect sizes were computed, study quality was evaluated, and random effects models were used to estimate sampling error and population variance of the observed effects.

RESULTS:

Exercise training significantly reduced depressive symptoms by a heterogeneous mean effect size delta (Δ) of 0.30 (95% CI, 0.25-0.36). Larger antidepressant effects were obtained when (1) baseline depressive symptoms were higher, (2) patients met recommended physical activity levels, and (3) the trial primary outcome, predominantly function related, was significantly improved among patients having baseline depressive symptoms indicative of mild-to-moderate depression.

CONCLUSIONS:

Exercise reduces depressive symptoms among patients with a chronic illness. Patients with depressive symptoms indicative of mild-to-moderate depression and for whom exercise training improves function-related outcomes achieve the largest antidepressant effects.

Abstract

Background

Pay-for-performance (P4P) is increasingly implemented in the healthcare system to encourage improvements in healthcare quality. P4P is a payment model that rewards healthcare providers for meeting pre-established targets for delivery of healthcare services by financial incentives. Based on their performance, healthcare providers receive either additional or reduced payment. Currently, little is known about P4P schemes intending to improve delivery of chronic care through disease management. The objectives of this paper are therefore to provide an overview of P4P schemes used to stimulate delivery of chronic care through disease management and to provide insight into their effects on healthcare quality and costs.

Methods

A systematic PubMed search was performed for English language papers published between 2000 and 2010 describing P4P schemes related to the implementation of disease management. Wagner's chronic care model was used to make disease management operational.

Results

Eight P4P schemes were identified, introduced in the USA (n = 6), Germany (n = 1), and Australia (n = 1). Five P4P schemes were part of a larger scheme of interventions to improve quality of care, whereas three P4P schemes were solely implemented. Most financial incentives were rewards, selective, and granted on the basis of absolute performance. More variation was found in incented entities and the basis for providing incentives. Information about motivation, certainty, size, frequency, and duration of the financial incentives was generally limited. Five studies were identified that evaluated the effects of P4P on healthcare quality. Most studies showed positive effects of P4P on healthcare quality. No studies were found that evaluated the effects of P4P on healthcare costs.

Conclusion

The number of P4P schemes to encourage disease management is limited. Hardly any information is available about the effects of such schemes on healthcare quality and costs.

Abstract

Background

Primary care practices provide a gate-keeping function in many health care systems. Since depressive disorders are highly prevalent in primary care settings, reliable detection and diagnoses are a first step to enhance depression care for patients. Provider training is a self-evident approach to enhance detection, diagnoses and treatment options and might even lead to improved patient outcomes.

Methods

A systematic literature search was conducted reviewing research studies providing training of general practitioners, published from 1999 until May 2011, available on the electronic databases Medline, Web of Science, PsycINFO and the Cochrane Library as well as national guidelines and health technology assessments (HTA).

Results

108 articles were fully assessed and 11 articles met the inclusion criteria and were included. Training of providers alone (even in a specific interventional method) did not result in improved patient outcomes. The additional implementation of guidelines and the use of more complex interventions in primary care yield a significant reduction in depressive symptomatology. The number of studies examining sole provider training is limited, and studies include different patient samples (new on-set cases vs. chronically depressed patients), which reduce comparability.

Conclusions

This is the first overview of randomized controlled trials introducing GP training for depression care. Provider training by itself does not seem to improve depression care; however, if combined with additional guidelines implementation, results are promising for new-onset depression patient samples. Additional organizational structure changes in form of collaborative care models are more likely to show effects on depression care.

Keywords:

depression; primary care; training; health service

Saw Palmetto, even in high dose, has no benefit for lower urinary tract symptoms, according to this recent study.

Drats!

Abstract and Introduction

Abstract

Background Coffee contains many biologically active compounds, including caffeine and phenolic acids, that have potent antioxidant activity and can affect glucose metabolism and sex hormone levels. Because of these biological activities, coffee may be associated with a reduced risk of prostate cancer.
Methods We conducted a prospective analysis of 47 911 men in the Health Professionals Follow-up Study who reported intake of regular and decaffeinated coffee in 1986 and every 4 years thereafter. From 1986 to 2006, 5035 patients with prostate cancer were identified, including 642 patients with lethal prostate cancers, defined as fatal or metastatic. We used Cox proportional hazards models to assess the association between coffee and prostate cancer, adjusting for potential confounding by smoking, obesity, and other variables. All P values were from two-sided tests.
Results The average intake of coffee in 1986 was 1.9 cups per day. Men who consumed six or more cups per day had a lower adjusted relative risk for overall prostate cancer compared with nondrinkers (RR = 0.82, 95% confidence interval [CI] = 0.68 to 0.98, P _trend = .10). The association was stronger for lethal prostate cancer (consumers of more than six cups of coffee per day: RR = 0.40, 95% CI = 0.22 to 0.75, P _trend = .03). Coffee consumption was not associated with the risk of nonadvanced or low-grade cancers and was only weakly inversely associated with high-grade cancer. The inverse association with lethal cancer was similar for regular and decaffeinated coffee (each one cup per day increment: RR = 0.94, 95% CI = 0.88 to 1.01, P = .08 for regular coffee and RR = 0.91, 95% CI = 0.83 to 1.00, P = .05 for decaffeinated coffee). The age-adjusted incidence rates for men who had the highest (≥6 cups per day) and lowest (no coffee) coffee consumption were 425 and 519 total prostate cancers, respectively, per 100 000 person-years and 34 and 79 lethal prostate cancers, respectively, per 100 000 person-years.
Conclusions We observed a strong inverse association between coffee consumption and risk of lethal prostate cancer. The association appears to be related to non-caffeine components of coffee.

Introduction

Coffee contains diverse biologically active compounds that include caffeine, minerals, and phytochemicals. Long-term coffee drinking has been associated with improved glucose metabolism and insulin secretion in observational and animal studies.^[1] Coffee is also a potent antioxidant^[2–4] and may be associated with sex hormone levels.^[5–7]

Coffee consumption has been consistently associated with a reduced risk of type 2 diabetes,^[8] and its effects on insulin, sex hormones, and antioxidants may also be relevant to prostate cancer. We hypothesized that coffee may be associated with lower risk of more advanced prostate cancers because the associations of insulin, antioxidants, and androgens with incidence of prostate cancer are stronger for advanced disease than for overall disease.^[9–15]

Epidemiological studies of coffee consumption and prostate cancer have generally reported null results,^[16–30] although most lacked a wide range of coffee intakes and a large number of case subjects and none specifically examined advanced disease. The two studies of coffee consumption and prostate cancer mortality^[31,32] found no statistically significant associations, but these were limited by a narrow range of intake, small number of cancer deaths, and inadequate adjustment for potential confounding.

We investigated the relationship between coffee intake and risk of overall prostate cancer and of aggressive disease, defined as lethal, advanced, or high-grade cancer, in the Health Professionals Follow-up Study.

Section 1 of 4

Next: Methods  » Abstract and Introduction Methods Results Discussion

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References

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Table 1. Age-adjusted characteristics of the Health Professionals Follow-up Study population at baseline in 1986, by coffee consumption*

Characteristic	Category of total coffee intake
	None (n = 7890)	<1 cup per day (n = 9533)	1–3 cups per day (n = 21 261)	4–5 cups per day (n = 6735)	≥6 cups day (n = 2492)
Mean age, y	52	55	55	54	53
White race, %	95	94	96	98	98
Mean BMI, kg/m2	25	25	26	26	26
Mean BMI at age 21, kg/m2	23	23	23	23	23
Mean height, inches	70	70	70	70	70
Former smoker, quit >10 y ago, %	20	28	32	34	31
Former smoker, quit ≤10 y ago, %	6	10	14	17	17
Current smokers, %	4	6	10	16	25
Vigorous activity (% highest quintile)	17	17	15	15	11
Diabetes, %	3	3	3	3	3
Family history of prostate cancer, %	13	11	12	12	12
PSA test, 1994, %	35	39	38	38	33
PSA test, 2004, %	60	64	66	66	58
Mean dietary intakes
Energy, kcal/d	1960	1895	1990	2069	2159
Alcohol, g/d	6	9	13	14	15
Calcium, mg/d	973	931	866	881	873
Alpha-linolenic acid, g/d	1.1	1.1	1.1	1.1	1.1
Supplemental vitamin E, mg/day	41.5	45.1	36.1	33.3	33.0
Multivitamin use, %	42	44	41	40	38
Processed meat, servings per week	2.1	2.1	2.6	2.9	3.4
Tomato sauce, servings per week	0.9	0.9	0.9	0.9	0.9
Total coffee, servings per day	0.0	0.5	1.9	4.2	6.3
Regular coffee, servings per day	0.0	0.2	1.3	2.9	4.2
Decaffeinated coffee, servings per day	0.0	0.2	0.6	1.3	2.0

* All variables (except age) are standardized to the age distribution of the cohort at baseline. BMI = body mass index; PSA = prostate-specific antigen.

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Table 2. Relative risk (RR) with 95% confidence interval (95% CI) of prostate cancer by category of total coffee intake, 1986–2006*

Risk of prostate cancer	Category of coffee intake					P trend
	None	<1 cup/d	1–3 cups/d	4–5 cups/d	≥6 cups/d
All prostate cancers, No.	587	1139	2438	719	152
Age-adjusted RR (95% CI)	1.00	0.96 (0.87 to 1.06)	0.97 (0.88 to 1.06)	0.95 (0.85 to 1.06)	0.81 (0.67 to 0.96)	.08
Fully adjusted RR (95% CI)	1.00	0.94 (0.85 to 1.05)	0.94 (0.86 to 1.04)	0.93 (0.83 to 1.04)	0.82 (0.68 to 0.98)	.10
Lethal prostate cancers†, No.	89	150	298	93	12
Age-adjusted RR (95% CI)	1.00	0.76 (0.58 to 0.99)	0.73 (0.58 to 0.93)	0.83 (0.62 to 1.11)	0.43 (0.24 to 0.80)	.08
Fully adjusted RR (95% CI)	1.00	0.76 (0.58 to 1.00)	0.71 (0.55 to 0.92)	0.76 (0.56 to 1.04)	0.40 (0.22 to 0.75)	.03
Advanced prostate cancers†, No.	122	211	422	122	19
Age-adjusted RR (95% CI)	1.00	0.81 (0.65 to 1.02)	0.78 (0.63 to 0.95)	0.79 (0.61 to 1.01)	0.49 (0.30 to 0.80)	.01
Fully adjusted RR (95% CI)	1.00	0.81 (0.64 to 1.02)	0.75 (0.60 to 0.93)	0.73 (0.56 to 0.95)	0.47 (0.28 to 0.77)	.004
Nonadvanced prostate cancers†, No.	353	729	1554	483	102
Age-adjusted RR (95% CI)	1.00	1.04 (0.91 to 1.18)	1.04 (0.92 to 1.16)	1.04 (0.91 to 1.20)	0.88 (0.71 to 1.10)	.60
Fully adjusted RR(95% CI)	1.00	1.01 (0.88 to 1.15)	0.99 (0.87 to 1.12)	1.02 (0.88 to 1.18)	0.93 (0.74 to 1.16)	.77
Grade 8–10 cancers, No.	61	111	255	78	11
Age-adjusted RR (95% CI)	1.00	0.86 (0.63 to 1.18)	0.93 (0.70 to 1.23)	0.96 (0.69 to 1.35)	0.57 (0.30 to 1.09)	.58
Fully adjusted RR (95% CI)	1.00	0.84 (0.61 to 1.16)	0.87 (0.65 to 1.18)	0.88 (0.61 to 1.26)	0.53 (0.27 to 1.02)	.29
Grade 7 cancers, No.	174	295	641	226	41
Age-adjusted RR (95% CI)	1.00	0.86 (0.72 to 1.04)	0.88 (0.74 to 1.04)	0.98 (0.80 to 1.20)	0.69 (0.49 to 0.97)	.58
Fully adjusted RR (95% CI)	1.00	0.85 (0.70 to 1.04)	0.85 (0.71 to 1.02)	0.94 (0.76 to 1.16)	0.69 (0.49 to 0.99)	.50
Grade 2–6 cancers, No.	232	489	1045	298	70
Age-adjusted RR (95% CI)	1.00	1.08 (0.92 to 1.26)	1.07 (0.93 to 1.24)	0.99 (0.83 to 1.18)	0.94 (0.72 to 1.23)	.34
Fully adjusted RR (95% CI)	1.00	1.02 (0.87 to 1.20)	1.01 (0.87 to 1.18)	0.96 (0.80 to 1.15)	1.00 (0.75 to 1.31)	.53

* All relative risks are from an age-adjusted model adjusted for age in months and calendar time. The multivariable model was additionally adjusted for: race (White, African American, Asian American, Other), height (quartiles), BMI at age 21 (<20, 20 to <22.5, 22.5 to <25, ≥25), current BMI (<21, 21 to <23, 23 to <25, 25 to <27.5, 27.5 to <30, ≥30 kg/m²), vigorous physical activity (quintiles), smoking (never, former quit >10 years ago, former quit <10 years ago, current), diabetes (type I or II, yes/no), family history of prostate cancer in father or brother (yes/no), multivitamin use (yes/no), intakes of processed meat, tomato sauce, calcium, alpha linolenic acid, supplemental vitamin E, alcohol intake (all quintiles), and energy intake (continuous), and history of PSA testing (yes/no, lagged by one period to avoid counting diagnostic PSA tests as screening; collected frsom 1994 onwards). All P values were from two-sided tests. BMI = body mass index; PSA, prostate-specific antigen.
† Lethal prostate cancer: Prostate cancer death or bone metastases at diagnosis or during follow-up. Advanced: Lethal, or stage T3b, T4, N1, or M1 at diagnosis, or spread to lymph nodes or other metastases during follow-up. Nonadvanced: T1 or T2 and N0/M0 at diagnosis with no spread to lymph nodes or other metastases or death during follow-up.

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Table 3. Relative risk (RR) and 95% confidence interval (95% CI) of prostate cancer by category of regular coffee intake*

Risk of prostate cancer	No coffee at all†	Category of regular (with caffeine) coffee intake				P trend	No regular, some decaf
		<1 cup per day	1–3 cups per day	4–5 cups per day	≥6 cups per day
Lethal prostate cancers‡, No.	89	207	209	52	6		79
Fully adjusted RR (95% CI)*	1.00	0.81 (0.61 to 1.07)	0.71 (0.54 to 0.93)	0.77 (0.53 to 1.10)	0.46 (0.20 to 1.08)	.07	0.72 (0.51 to 1.01)
Advanced prostate cancers‡, No.	122	298	293	65	12		106
Fully adjusted RR (95% CI)*	1.00	0.86 (0.69 to 1.09)	0.74 (0.59 to 0.93)	0.70 (0.51 to 0.95)	0.69 (0.38 to 1.27)	.01	0.75 (0.56 to 1.00)
Nonadvanced prostate cancers‡, No.	353	1042	1164	270	43		349
Fully adjusted RR (95% CI)*	1.00	0.98 (0.86 to 1.12)	0.99 (0.87 to 1.12)	1.00 (0.84 to 1.18)	0.93 (0.67 to 1.29)	.97	1.10 (0.93 to 1.29)

* All relative riskss are from a multivariable model adjusted for: age in months, calendar time, race (White, African American, Asian American, Other), height (quartiles), BMI at age 21 (four categories), current BMI (six categories), vigorous physical activity (quintiles), smoking (never, former quit >10 years ago, former quit <10 years ago, current), diabetes (type I or II, yes/no), family history of prostate cancer in father or brother (yes/no), multivitamin use (yes/no), intakes of processed meat, tomato sauce, calcium, alpha linolenic acid, supplemental vitamin E, alcohol intake (all quintiles), energy intake (continuous), and history of prostate-specific antigen testing. Models for regular coffee are also adjusted for decaffeinated coffee intake (continuous). All P values are from two-sided tests. BMI = body mass index.
† Reference group is men who drink no regular or decaffeinated coffee.
‡ Lethal prostate cancer: Prostate cancer death or bone metastases at diagnosis or during follow-up. Advanced: Lethal, or stage T3b, T4, N1, or M1 at diagnosis, or spread to lymph nodes or other metastases during follow-up. Nonadvanced: T1 or T2 and N0/M0 at diagnosis with no spread to lymph nodes or other metastases or death during follow-up.

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Table 4. Relative risk (RR) and 95% confidence interval (CI) of prostate cancer by category of decaffeinated coffee intake*

	No coffee at all†	Category of decaffeinated coffee intake			P trend	No decaf, some regular
		<1 cup/d	1–3 cups/d	≥4 cups/d
Lethal prostate cancers‡, No.	89	264	125	15		149
Fully adjusted RR*	1.00	0.81 (0.62 to 1.06)	0.68 (0.50 to 0.91)	0.53 (0.30 to 0.94)	.01	0.71 (0.52 to 0.98)
Advanced prostate cancers‡, No	122	374	171	25		204
Fully adjusted RR*	1.00	0.85 (0.68 to 1.07)	0.70 (0.54 to 0.89)	0.67 (0.43 to 1.05)	.02	0.77 (0.59 to 1.01)
Nonadvanced prostate cancers‡, No.	353	1455	688	86		639
Fully adjusted RR*	1.00	0.99 (0.87 to 1.13)	1.04 (0.90 to 1.19)	0.94 (0.74 to 1.20)	.88	0.98 (0.85 to 1.14)

* All relative riskss are from a multivariable model adjusted for: age in months, calendar time, race (White, African American, Asian American, Other), height (quartiles), BMI at age 21 (four categories), current BMI (six categories), vigorous physical activity (quintiles), smoking (never, former quit >10 years ago, former quit <10 years ago, current), diabetes (type I or II, yes/no), family history of prostate cancer in father or brother (yes/no), multivitamin use (yes/no), intakes of processed meat, tomato sauce, calcium, alpha linolenic acid, supplemental vitamin E, alcohol intake (all quintiles), and energy intake (continuous), and history of prostate-specific antigen testing. Models for decaffeinated coffee are also adjusted for regular coffee intake (continuous). All P values are from two-sided tests. BMI = body mass index.
† Reference group is men who drink no regular or decaffeinated coffee. ‡ Lethal prostate cancer: Prostate cancer death or bone metastases at diagnosis or during follow-up. Advanced: Lethal, or stage T3b, T4, N1 or M1 at diagnosis, or spread to lymph nodes or other metastases during follow-up. Nonadvanced: T1 or T2 and N0/M0 at diagnosis with no spread to lymph nodes or other metastases or death during follow-up.

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Table 5. Relative risk (RR) and 95% confidence interval (95% CI) of prostate cancer by category of total coffee intake for various latency periods between exposure and diagnosis*

	Total prostate cancer		Advanced cancer†		Nonadvanced cancer†
	N	RR (95% CI)	N	RR (95% CI)	N	RR (95% CI)
0 to 4-year lag, cups per day
None	810	1.00 (referent)	160	1.00 (referent)	493	1.00 (referent)
<1	1003	.95 (.87 to 1.05)	180	.78 (.62 to.97)	655	1.05 (.93 to 1.18)
1–3	2501	.96 (.89 to 1.05)	436	.77 (.63 to.93)	1592	1.01 (.91 to 1.13)
4–5	587	.97 (.87 to 1.09)	100	.73 (.56 to.95)	389	1.08 (.93 to 1.24)
≥6	134	.81 (.67 to.98)	20	.52 (.33 to.84)	92	.96 (.76 to 1.21)
P trend		.20		.008		.91
4 to 8-year lag, cups per day
None	745	1.00 (referent)	131	1.00 (referent)	468	1.00 (referent)
<1	886	.92 (.83 to 1.02)	152	.84 (.66 to 1.07)	589	1.00 (.88 to 1.13)
1–3	2267	.93 (.85 to 1.02)	329	.72 (.58 to.89)	1519	1.00 (.89 to 1.11)
4–5	594	.92 (.82 to 1.03)	99	.81 (.61 to 1.07)	397	.97 (.85 to 1.12)
≥6	153	.80 (.67 to.96)	18	.47 (.28 to.78)	102	.88 (.71 to 1.10)
P trend		.06		.008		.34
8 to 12-year lag, cups per day
None	551	1.00 (referent)	79	1.00 (referent)	360	1.00 (referent)
<1	664	.98 (.87 to 1.10)	91	.85 (.62 to 1.17)	458	1.06 (.92 to 1.22)
1–3	1687	.99 (.89 to 1.10)	181	.68 (.51 to.91)	1175	1.06 (.93 to 1.20)
4–5	465	.91 (.80 to 1.03)	63	.82 (.58 to 1.17)	329	.98 (.83 to 1.14)
≥6	154	.93 (.77 to 1.12)	18	.71 (.42 to 1.21)	111	1.04 (.83 to 1.30)
P trend		.17		.18		.70
12 to 16-year lag, cups per day
None	389	1.00 (referent)	41	1.00 (referent)	268	1.00 (referent)
<1	448	.97 (.84 to 1.11)	49	.90 (.58 to 1.39)	307	.96 (.81 to 1.14)
1–3	1046	.93 (.82 to 1.06)	93	.72 (.48 to 1.07)	742	.94 (.81 to 1.10)
4–5	353	.97 (.83 to 1.13)	41	.97 (.61 to 1.55)	260	1.02 (.85 to 1.23)
≥6	115	.93 (.75 to 1.16)	8	.59 (.27 to 1.29)	84	.98 (.76 to 1.26)
P trend		.61		.43		.78

* All relative riskss are from multivariable models adjusted for: age in months, calendar time, race (White, African American, Asian American, Other), height (quartiles), BMI at age 21 (<20, 20 to <22.5, 22.5 to <25, .25 kg/m²), current BMI (<21, 21 to <23, 23 to <25, 25 to <27.5, 27.5 to <30, .30 kg/m²), vigorous physical activity (quintiles), smoking (never, former quit >10 years ago, former quit <10 years ago, current), diabetes (type I or II, yes/no), family history of prostate cancer in father or brother (yes/no), multivitamin use (yes/no), intakes of processed meat, tomato sauce, calcium, alpha linolenic acid, supplemental vitamin E, alcohol intake (all quintiles), and energy intake (continuous), and history of PSA testing (yes/no, lagged by one period to avoid counting diagnostic PSA tests as screening; collected from 1994 onwards). All P values are from two-sided tests. BMI = body mass index; PSA = prostate-specific antigen.
† Advanced: Lethal, or stage T3b, T4, N1, or M1 at diagnosis, or spread to lymph nodes or other metastases during follow-up. Nonadvanced: T1 or T2 and N0/M0 at diagnosis with no spread to lymph nodes or other metastases or death during follow-up.

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Authors and Disclosures

Kathryn M. Wilson, Julie L. Kasperzyk, Jennifer R. Rider, Stacey Kenfield, Rob M. van Dam, Meir J. Stampfer, Edward Giovannucci and Lorelei A. Mucci

Department of Epidemiology (KMW, JLK, SK, MJS, EG, LAM) and Department of Nutrition (RMvD, MJS, EG), Harvard School of Public Health, Boston, MA; Channing Laboratory, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (KMW, JLK, JRR, SK, MJS, EG, LAM); Department of Urology, Örebro University Hospital, Örebro, Sweden (JRR); Department of Epidemiology and Department of Public Health and Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore (RMvD)

Correspondence to
Kathryn M. Wilson, ScD, Department of Epidemiology, Harvard School of Public Health, 677 Huntington Ave, Boston, MA 02115 (e-mail: kwilson@hsph.harvard.edu).

The NHS needs a major overhaul if the UK is to cope with the needs of people with long term conditions, according to Sir John Oldham.

Sir John is in charge of the team which aims to improve how the national health service deals with Long Term Conditions and Urgent Care.

Sir John established the collaboratives in the UK and was instrumental in their introduction to Australia.

Cf http://www.inpharm.com/news/163372/chronic-problem-health-service

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http://www.guardian.co.uk/healthcare-network/2011/jun/14/nhs-reform-around-lo...

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The STOPP criteria are available at http://www.em-consulte.com/showarticlefile/245669/main.pdf

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