The goal of this study was to perform a systematic review and meta-analysis to examine the effect of pre-existing diabetes on breast cancer-related outcomes.
We searched EMBASE and MEDLINE databases ...from inception through July 1, 2009, using search terms related to diabetes mellitus, cancer, and prognostic outcome. Studies were included if they reported a prognostic outcome by diabetes status, evaluated a cancer population, and contained original data published in the English language. We performed a meta-analysis of pre-existing diabetes and its effect on all-cause mortality in patients with breast cancer and qualitatively summarized other prognostic outcomes.
Of 8,828 titles identified, eight articles met inclusion/exclusion criteria and described outcomes in patients with breast cancer and diabetes. Pre-existing diabetes was significantly associated with all-cause mortality in six of seven studies. In a meta-analysis, patients with breast cancer and diabetes had a significantly higher all-cause mortality risk (pooled hazard ratio HR, 1.49; 95% CI, 1.35 to 1.65) compared with their nondiabetic counterparts. Three of four studies found pre-existing diabetes to be associated with more advanced stage at presentation. Diabetes was also associated with altered regimens for breast cancer treatment and increased toxicity from chemotherapy.
Compared with their nondiabetic counterparts, patients with breast cancer and pre-existing diabetes have a greater risk of death and tend to present at later stages and receive altered treatment regimens. Studies are needed to investigate pathophysiologic interactions between diabetes and breast cancer and determine whether improvements in diabetes care can reduce mortality in patients with breast cancer.
Screening for breast cancer Peairs, Kimberly S; Choi, Youngjee; Stewart, Rosalyn W ...
Seminars in oncology,
02/2017, Letnik:
44, Številka:
1
Journal Article
Recenzirano
This review will give a general overview of the impact of breast cancer, as well as breast cancer risk factors, identification of high-risk groups, screening modalities, and guidelines for screening ...average-risk and high-risk individuals, including a case discussion of the primary care provider's approach to screening.
Diabetes mellitus appears to be a risk factor for some cancers, but the effect of preexisting diabetes on all-cause mortality in newly diagnosed cancer patients is less clear.
To perform a systematic ...review and meta-analysis comparing overall survival in cancer patients with and without preexisting diabetes.
We searched MEDLINE and EMBASE through May 15, 2008, including references of qualifying articles.
English-language, original investigations in humans with at least 3 months of follow-up were included. Titles, abstracts, and articles were reviewed by at least 2 independent readers. Of 7858 titles identified in our original search, 48 articles met our criteria.
One reviewer performed a full abstraction and other reviewers verified accuracy. We contacted authors and obtained additional information for 3 articles with insufficient reported data.
Studies reporting cumulative survival rates were summarized qualitatively. Studies reporting Cox proportional hazard ratios (HRs) or Poisson relative risks were combined in a meta-analysis. A random-effects model meta-analysis of 23 articles showed that diabetes was associated with an increased mortality HR of 1.41 (95% confidence interval CI, 1.28-1.55) compared with normoglycemic individuals across all cancer types. Subgroup analyses by type of cancer showed increased risk for cancers of the endometrium (HR, 1.76; 95% CI, 1.34-2.31), breast (HR, 1.61; 95% CI, 1.46-1.78), and colorectum (HR, 1.32; 95% CI, 1.24-1.41).
Patients diagnosed with cancer who have preexisting diabetes are at increased risk for long-term, all-cause mortality compared with those without diabetes.
Screening for colorectal cancer Choi, Youngjee; Sateia, Heather F; Peairs, Kimberly S ...
Seminars in oncology,
02/2017, Letnik:
44, Številka:
1
Journal Article
Recenzirano
This review will comprise a general overview of colorectal cancer (CRC) screening. We will cover the impact of CRC, CRC risk factors, screening modalities, and guideline recommendations for screening ...in average-risk and high-risk individuals. Based on this data, we will summarize our approach to CRC screening.
Purpose
The optimal delivery of survivorship care, particularly within primary care, remains poorly understood. We established the Johns Hopkins Primary Care for Cancer Survivors (PCCS) clinic in ...2015 to address care challenges unique to cancer survivors. To better understand the care from the PCCS clinic, we interviewed patients about their perception of care delivery, survivorship care, and care coordination.
Methods
We conducted semi-structured interviews with adult survivors of any cancer type seen in the PCCS clinic. A priori and in vivo coding of verbatim transcripts was part of the thematic analysis.
Results
Seventeen cancer survivors were interviewed (ages 37–78). Themes that emerged were (1) optimal care and (2) the PCCS experience. Subthemes respectively included the ideal role of the primary care provider (1), telehealth/COVID-19 challenges and opportunities (1), patient-derived value from the PCCS clinic (2), and improving the PCCS model (2). Overall, PCCS patients expected and experienced high-quality, comprehensive primary care by providers with cancer survivorship expertise. Patients reported telehealth benefits and challenges for survivorship care during the COVID-19 pandemic.
Conclusions
PCCS patients perceived receiving high-quality primary care and valued being seen in a primary care–based survivorship clinic. The PCCS clinic can serve as a model of primary care–based cancer survivorship.
Implications for Cancer Survivors
Ideal primary care provider roles and care coordination are important factors for high-quality survivorship care and can be provided by a specialized cancer survivorship clinic in primary care.
To examine how care for breast cancer survivors compares with controls.
Using the Surveillance, Epidemiology, and End Results-Medicare database, we examined five cohorts of stages 1 to 3 breast ...cancer survivors diagnosed from 1998 to 2002. For each survivor cohort (defined by diagnosis year), we calculated the number of visits to oncology specialists, primary care providers (PCPs), and other physicians and the percentage who received influenza vaccination, cholesterol screening, colorectal cancer screening, bone densitometry, and mammography during survivorship year 1 (days 366 to 730 postdiagnosis). We compared survivors' care to that of five cohorts of screening controls who were matched to survivors on age, ethnicity, sex, and region and who had a mammogram in the survivor's year of diagnosis and to that of five cohorts of comorbidity controls who were matched on age, ethnicity, sex, region, and comorbidity. We examined whether survivors' care was associated with the mix of physician specialties that were visited.
A total of 23,731 survivors were matched with 23,731 screening controls and 23,396 comorbidity controls. There was no difference in trends over time in PCP visits between survivors and either control group. The survivors' rate of increase in other physician visits was greater than screening controls (P = .002) but was no different from comorbidity controls. Survivors were less likely to receive preventive care than screening controls but were more likely than comorbidity controls. Trends over time in survivors' care tended to be better than screening controls but were no different than comorbidity controls. Survivors who visited both a PCP and oncology specialist were most likely to receive recommended care.
Involvement by both PCPs and oncology specialists can facilitate appropriate care for survivors.
BACKGROUND
Deficiencies in care for cancer survivors may result from unclear roles for primary care providers (PCPs) and oncology specialists in follow-up.
OBJECTIVES
To compare cancer survivors’ ...care to non-cancer controls.
DESIGN
Retrospective, longitudinal, controlled study starting 366 days post-diagnosis.
SUBJECTS
Stage 1-3 breast cancer survivors age 65+ diagnosed in 1998 (n = 1961) and matched non-cancer controls (n = 1961).
MEASUREMENTS
Using the SEER-Medicare database, we examined the number of visits to PCPs, oncology specialists, and other physicians; receipt of influenza vaccination, cholesterol screening, colorectal cancer screening, bone densitometry, and mammography; and whether care receipt was associated with physician mix visited.
RESULTS
Survivors were consistently less likely to receive influenza vaccination, cholesterol screening, colorectal cancer screening, and bone densitometry but more likely to receive mammograms than controls (all p < 0.05). Over time, colorectal cancer screening and mammography decreased and influenza vaccination increased for both groups (all p < 0.0001). Trends over time in care receipt were similar for survivors and controls. In Year 1, survivors had more visits to PCPs but fewer visits to other physicians than controls (both p < 0.05). Over time, survivors’ visits to PCPs and other physicians increased and to oncology specialists decreased (all p < 0.0001). Controls’ visits to PCPs increased (p < 0.0001) faster than survivors’ (p = 0.003). Controls’ visits to other physicians increased (p < 0.0001) at a rate similar to survivors. Survivors who visited both a PCP and oncology specialist were most likely to receive each service.
CONCLUSIONS
Better coordination between PCPs and oncology specialists may improve care for older breast cancer survivors.
Abstract
Background
Survivorship care plans seek to improve the transition to survivorship, but the required resources present implementation barriers. This randomized controlled trial aimed to ...identify the simplest, most effective approach for survivorship care planning.
Methods
Stage 1-3 breast, colorectal, and prostate cancer patients aged 21 years or older completing treatment were recruited from an urban-academic and rural-community cancer center. Participants were randomly assigned, stratified by recruitment site and cancer type 1:1:1 to a mailed plan, plan delivered during a 1-time transition visit, or plan delivered during a transition visit plus 6-month follow-up visit. Health service use data were collected from participants and medical records for 18 months. The primary outcome, receipt of all plan-recommended care, was compared across intervention arms using logistic regression adjusting for cancer type and recruitment site, with P less than .05 considered statistically significant.
Results
Of 378 participants randomly assigned, 159 (42.1%) were breast, 142 (37.6%) prostate, and 77 (20.4%) colorectal cancer survivors; 207 (54.8%) from the academic site and 171 (45.2%) from the community site; 316 were analyzable for the primary outcome. There was no difference across arms in the proportion of participants receiving all plan-recommended care: 45.2% mail, 50.5% 1-visit, 42.7% 2-visit (2-sided P = .60). Adherence by cancer type for mail, 1-visit, and 2-visit, respectively, was 52.2%, 53.3%, and 40.0% for breast cancer; 48.6%, 64.1%, and 57.1% for prostate cancer; and 23.8%, 19.0%, and 26.1% for colorectal cancer. There were no statistically significant interactions by recruitment site or cancer type.
Conclusions
This study did not find differences in receipt of recommended follow-up care by plan delivery approach. Feasibility and other factors may determine the best approach for survivorship care planning.
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