CanPrevent Conference Breakout Session Article Summaries & Guiding Questions
Dr. Kristan Aronson - Primary Prevention: Identifying and reducing environmental risk factors for cancer, particularly light at night ! !
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Breast Cancer Management
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Causes of breast cancer: could work at night really be a cause? Guiding Questions: 1) Do you know of any actions that have been taken in addressing primary prevention research – to reduce exposure to other risk factors? 2) Does research on one specific risk factor (say long-term shift work) ever end?
“Strategies are urgently needed to inform women, their doctors and employers on the risks associated with long-term light-at-night exposure.”
Kristan J Aronson*,1, Anne Grundy2, Jill Korsiak1 & John J Spinelli3,4 Family doctors interested in why the 60-year-old woman in front of them has recently been diagnosed with breast cancer might consider asking her if she worked at night during her career. Even the surgeon may be disconcerted because this woman does not have any of the known risk factors: she has no family history, had two children in her twenties, she eats well, exercises, drinks little alcohol and was a regular participant in breast cancer screening. At the same time, most physicians have experienced the disruption that occurs when they work at night, and perhaps all have suffered jet lag at some point. These activities that require light in times of natural darkness or adaptation to new time zones can indeed disrupt our internal clock, our circadian rhythms. How could exposure to light at night cause increased breast cancer risk? In addition to the established and long-suspected factors that increase a woman’s risk of breast cancer [1] , in the past 10 years or so there has been more research on how a woman’s career could be associated with breast cancer. Some established cohorts of
nurses in the USA and Europe and other studies began to produce evidence relating to the hypothesis originally expounded in 1987 [2] that exposure to light at night could disrupt circadian (daily) rhythms and increase cancer risk. The biologic pathway from light exposure to cancer that has been investigated most frequently is melatonin, a hormone produced in the pineal gland and at its peak each night if we sleep in a ‘normal’ pattern in the dark. If we are instead awake and exposed to light at night through activities including night work, melatonin production will decrease and its positive properties including tumor suppression will subsequently be hindered. There is some support for the melatonin pathway from light to cancer risk, but other mechanisms have also been hypothesized such as reduced vitamin D exposure, poor sleep quality, changes in metabolism and a disconnect within your body between centrally timed functions and the more peripherally timed bodily functions [3] . So while it is agreed that, from a biological point of view, various pathways from
KEYWORDS
s breast cancer s environment s exposure s occupation s risk
“In 2007, an expert panel at the International Agency for Research on Cancer came to the consensus that long-term shift work causing circadian disruption should be labeled as a ‘probable carcinogen’.”
Division of Cancer, Care & Epidemiology, Cancer Research Institute, Queen’s University, Kingston, Ontario, Canada Department of Cancer, Epidemiology & Prevention Research, Alberta Health Services, Cancer Control, Alberta, Calgary, Alberta, Canada 3 Cancer Control Research, British Columbia Cancer Agency, Vancouver, British Columbia, Canada 4 School of Population & Public Health, University of British Columbia, Vancouver, British Columbia, Canada *Author for correspondence: aronson@queensu.ca 1 2
10.2217/BMT.15.4 © 2015 Future Medicine Ltd
Breast Cancer Manag. (2015) 4(3), 125–127
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EDITORIAL Aronson, Grundy, Korsiak & Spinelli
“...breast cancer rates
among teachers in California were higher among women with greater outdoor light at night measured by satellite imagery.”
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light-at-night exposure to breast cancer are plausible and supported by strong experimental evidence, the evidence from human studies is more contradictory and continues to evolve. In 2007, an expert panel at the International Agency for Research on Cancer came to the consensus that long-term shift work causing circadian disruption should be labeled as a ‘probable carcinogen’ [4] . As a direct result, worker’s compensation was awarded in Denmark for women diagnosed with breast cancer who had worked long-term shift work, and other jurisdictions are currently considering a similar response. While it’s a great thing that research is paying more attention to working women and the particular occupational circumstances that might be related to increased breast cancer risk, studies would have more comparable results if their methods were able to capture all of the various patterns of shift work, including the patterns/ordering of nights and day shifts, number of consecutive nights, timing over the life course and cumulative duration [5] . Our study was able to do this and found a greater than doubling risk of breast cancer among those who had worked 30 years or more in jobs that included night work, and this increased risk was seen among both healthcare and other professional groups [6] . However, our studies among nurses currently working rotating shift patterns of day and night have failed to detect a strong relationship with decreased melatonin as the potential pathway in which shift workers are at increased breast cancer risk [7,8] . The relatively low light levels at night in our hospital workplace could possibly explain this finding, whereas occupational settings in the past may have had higher light levels at night. Furthermore, sex hormones [9] , physical activity or sedentary behavior [10,11] and genes [12] do not explain the increased breast cancer risk associated with shift workers. Now that we have accumulating evidence that night shift work is associated with increased breast cancer risk, as the quality and number of studies increase so too will our understanding of the precise circumstances that lead to increased risk. This in turn will help us develop safer worker health policies, such as recommending an upper limit to the duration of years of shift work. The precautionary principle asserts the need to protect us from harm, despite uncertainties in the evidence. Thus, preventive action can occur now and become more refined as high-quality evidence accumulates. In order to
Breast Cancer Manag. (2015) 4(3)
better characterize the association with breast cancer, new research needs to: be large enough to detect the risk if it exists, include health and non-healthcare night workers, have standardized measurement of light exposure, capture all the diverse patterns of work experience, and specify the exact timing of night work in the life course. In this way, research can clearly attribute breast cancer risk to specific workplace exposures and take into account the multitude of variables that could affect this association such as sleep, stress, medications and several other factors. Beyond investigating the role of nighttime light exposure in breast cancer risk, new research concerning other hypothesized mechanisms linking night shiftwork with breast cancer represents a promising avenue for research. While work evaluating the body of prospective evidence relating the hormone melatonin to breast cancer risk up to 2012 [13] suggested a protective effect for higher melatonin levels, more recent results from both a British cohort [13] and the Nurses Health Study II [14] have not supported this association. This highlights the potential importance of alternative pathways linking night shiftwork with breast cancer. Studies have begun exploring the role of circadian disruption more generally, with links between variations in circadian genes and breast cancer seen among nurses working at least three consecutive nights in Norway [15] , and differences in expression of circadian genes observed among shift workers compared with day workers in Italy [16] . New research also suggests a possible role of sleep disturbances, where among women in China both short ( 6 h) and long ( 9 h) sleep durations were linked to breast cancer risk among those with a history of shiftwork [17] . Further exploration of these pathways will improve our understanding of how night shiftwork is related to breast cancer risk and potentially provide alternate targets for intervention to reduce risk among women exposed to night work. In addition to night work per se, we are now at the point that we may need to consider outdoor lighting that could penetrate our bedrooms as well. For example, breast cancer rates among teachers in California were higher among women with greater outdoor light at night measured by satellite imagery [18] . More precise measurements of ambient light outside of residences is now available from other remote sensing sources [19,20] , and this improved precision
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Causes of breast cancer: could work at night really be a cause? in measurement of light at night will greatly advance the quality of epidemiologic studies investigating ambient light and cancer risk. Preventive strategies for breast cancer now also need to consider approaches to reduce long-term light-at-night exposure, incorporating this into health and workplace policy. Although physicians and healthcare workers are likely familiar with the various disruptions caused by shift work, assessing their patients for chronic light-at-night exposure as a risk factor for breast cancer is not routine. Strategies are urgently needed to inform women, their doctors and employers on the risks associated with long-term light-at-night exposure. Our research is strongly motivated by primary prevention, the concept that we can stop women from getting breast cancer by reducing or avoiding exposure. References 1
Howell A, Anderson AS, Clarke RB et al. Risk determination and prevention of breast cancer. Breast Cancer Res. 16, 446 (2014).
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Stevens RG. Electric power use and breast cancer: a hypothesis. Am J. Epidemiol. 125, 556–561 (1987).
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Fritschi L, Glass DC, Heyworth JS et al. Hypotheses for mechanisms linking shift work and cancer. Med. Hypotheses 77, 430–436 (2011). Straif K, Baan R, Grosse Y et al. Carcinogenicity of shift-work, painting, and fire-fighting. Lancet Oncol. 8(12), 1065–1066 (2007).
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Grundy A, Richardson H, Burstyn I et al. Increased risk of breast cancer associated with long-term shift work in Canada. Occup. Environ. Med. 70, 831–838 (2013).
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Grundy A, Sanchez M, Richardson H et al. Light intensity exposure, physical activity and biomarkers of melatonin among rotating shift nurses. Chronobiol. Int. 26, 1443–1461 (2009).
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These exciting new directions in research will allow us to better understand how factors like night work and light-at-night exposure increase a woman’s breast cancer risk, and results from high quality research will facilitate the development of cancer prevention policies that reduce the impact of this prevalent exposure. Financial & competing interests disclosure The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. No writing assistance was utilized in the production of this manuscript.
Grundy A, Tranmer J, Richardson H, Graham CH, Aronson KJ. The influence of light at night exposure on melatonin levels among Canadian rotating shift nurses. Cancer Epidemiol. Biomarkers Prev. 20, 2404–2412 (2011).
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Brown SB, Hankinson SE, Eliassen AH et al. Urinary melatonin concentration and the risk of breast cancer in Nurses’ Health Study I. Am. J. Epidemiol. 181(3), 155–162 (2015).
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Zienolddiny S, Haugen A, Lie JA, Anmarkrud KH, Kjaerheim K. Analysis of polymorphisms in the circadian-related genes and breast cancer risk in Norwegian nurses working night shifts. Breast Cancer Res. 15(4), R53 (2013).
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Langley A, Graham C, Grundy A, Tranmer J, Richardson H, Aronson KJ. A cross-sectional study of breast cancer biomarkers among shift working nurses. BMJ Open 2 , e000532 (2012).
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McPherson M, Janssen I, Grundy A, Tranmer J, Richardson H, Aronson KJ. Physical activity, sedentary behaviour and melatonin among rotating shift nurses. J. Occup. Environ. Med. 53(7), 716–721 (2011).
Bracci M, Manzella N, Copertaro A et al. Rotating-shift nurses after a day off: peripheral clock gene expression, urinary melatonin, and serum 17- -estradiol levels. Scand. J. Work Environ. Health 40(3), 295–304 (2014).
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Kobayashi L, Janssen I, Richardson H, Lai AS, Spinelli JJ, Aronson KJ. Moderate-to-vigorous intensity physical activity across the life course and risk of pre- and post-menopausal breast cancer. Breast Cancer Res. Treat. 139, 851–861 (2013).
Wang P, Ren F-M, Lin Y et al. Night shift work, sleep duration, daytime napping, and breast cancer risk. Sleep Medi. doi:11.017 (2014) (Epub ahead of print).
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Hurley S, Goldberg D, Nelson D et al. Light at night and breast cancer risk among California Teachers. Epidemiology 25, 697–706 (2014).
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Kyba C, Aronson KJ. Assessing exposure to outdoor lighting and health risks. Epidemiology doi:10.1097/EDE.0000000000000307 (2015) (Epub ahead of print).
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Kyba CC, Garz S, Kuechly H et al. Highresolution imagery of earth at night: New sources, opportunities and challenges. Remote Sensing 7, 1–23 (2015).
Stevens RG, Hansen J, Costa G et al. Considerations of circadian impact for defining shift work in cancer studies: IARC Working Group Report. Occup. Environ. Med. 68, 154–162 (2011).
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EDITORIAL
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Grundy A, Schuetz J, Lai AS et al. Shift work, clock gene variants and risk of breast cancer. Cancer Epidemiol. 37, 606–612 (2013).
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Wang X-S, Tipper S, Appleby PN, Allen NA, Key TJ, Travis RC. First-morning urinary melatonin and breast cancer risk in the Guernsey Study. Am. J. Epidemiol. 179(5), 584–593 (2014).
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Dr. Linda LĂŠvesque - Secondary Prevention: HPV Testing vs. PAP Screening !
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Article Summary: HPV Testing in Primary Cervical Screening: A Systematic Review and Meta-Analysis Objective: Previous findings have shown human papillomavirus (HPV) testing to be more sensitive than cytology testing for primary cervical screening. This systematic review aims to assess whether the increase in baseline detection with HPV testing corresponds to lower rates in subsequent screening rounds. Introduction: The purpose of screening is to reduce cervical cancer risk through the detection of lesions and to reduce the risk of advanced cancer through the detection of asymptomatic or early-stage cancer. Screening programs typically use either Papanicolaou smear test or cytology testing. Cytology testing has largely been responsible for the decline in cervical cancer over the past several decades. However, lack of progress in reducing cervical cancer incidence and the introduction of new technologies has created interest in alternatives. HPV testing as a primary screening test has been investigated as a possible way to improve the performance of cervical screening programs. For the adoption of HPV testing by cervical screening programs, it should have: - greater sensitivity than cytology for detecting existing high-grade cervical lesions, - reduced rates of high-grade lesions in subsequent screening rounds (because of detection and treatment of lesions that would have persisted in the absence of HPV testing), and - demonstrated safety of extended screening intervals for HPV-negative patients! This review uses relative detection rates (RDR) of potential cancer precursors from studies to explore whether the increased sensitivity with HPV testing is a result of over-detection of abnormalities that would regress with time or if it represents a lead-time gain. Methods: Medline, EMBASE, and the Cochrane Library were searched for randomized controlled trials, published from 2005 to 2010, that compared HPV-based and cytology-based cervical screening. Primary outcomes of interest were relative rates of higher grade cervical intraepithelial neoplasia (relative rates of CIN2, CIN2+, CIN3+) and invasive cervical cancer (incidence of and mortality due to invasive cervical cancer). Secondary outcomes included test performance characteristics (sensitivity, specificity, negative predictive value (NPV), and positive predictive value) and colposcopy referral rates. Results were pooled where possible using a random effects model. This was done because of the underlying assumption that different studies estimate different, yet related, intervention effects. RDRs were calculated as the CIN rate in the HPV testing (intervention) group divided by the CIN rate in the cytology (control subjects) group. RDRs over more than one screening round are used to explore whether higher sensitivity translates to a reduction in cervical cancer precursors and invasive cervical cancer over time. Results: Seven randomized trials were identified. Across studies, HPV testing was more accurate than conventional cytology and detected significantly more CIN3+ in the first screening round (M-H risk ratio 1.67; 95% CI 1.27 to 2.19) and significantly less in the second screening round (M-H RR 0.49; 95% CI 0.37 to 0.66). There were no differences in pooled rates of CIN2+ (M-H RR 1.19; 95% CI 0.94 to 1.50) and CIN3+(M-H RR 1.09; 95% CI 0.84 to 1.42), but there was a higher pooled rate of CIN2 (M-H RR 1.37; 95% CI 1.12 to 1.68) over two screening rounds. A trend towards lower rates of invasive cervical cancer was observed Discussion: Meta-analysis of trials with results reported for more than one round of screening was conducted. However, the results of the meta-analysis should be interpreted cautiously due to differences between trials in management of subjects and other factors. Overall, the findings indicate that HPV testing provided a means of earlier detection of clinically significant lesions. In this analysis, low rates of detection of CIN3+ at the second screening round in the intervention group and high NPVs in the studies that referred HPV- negative women for colposcopy indicates that lengthening the screening interval from two years to three years may be safe and feasible for HPV- negative women. Finding similar RDRs across multiple studies suggests that the findings are generalizable to the average-risk screening population in higher resource locations. Thus, organized screening programs in higher resource settings should consider adopting HPV testing as the primary screening test for women 30 or 35 years of age and older. More research is needed to determine what primary screening test is optimal for younger women, and at what age screening should be initiated.
WORKSHEET INCLUDING NOTES
CRITICAL APPRAISAL OF SYSTEMATIC REVIEWS / META-ANALYSES Prepared by: Dr. Linda LÊvesque, BScPhm, MSc, PhD Department of Community Health and Epidemiology, Queen’s University
PART A: ARE THE RESULTS VALID? Q1. Was the search for relevant studies detailed and exhaustive? a) Did authors search Medline, EMBASE & the Cochrane Trial registry? Authors of a systematic review should conduct a thorough search for studies that meet their inclusion criteria in order to minimize the possibility of selection bias. Studies have shown that restricting the search to Medline can result in publication bias (a type of selection bias). b) Did they check the reference list of retrieved articles? Searching bibliographic databases may not identify all relevant studies. Many of us have experienced finding relevant citations in the reference list of retrieved articles that somehow were not captured by our literature search. For this reason, authors of systematic reviews should check the reference lists of retrieved articles for additional publications that meet the inclusion criteria. c) Did they contact experts in the field to identify unpublished studies? Contacting experts in the field is important for identifying unpublished studies (to avoid publication bias), as well as those that may have been missed by the authors of the systematic review. d) Did they undertake a quantitative evaluation of publication bias? Publication bias occurs when the publication of research findings depends on the direction of the results (whether they favour the hypothesis under study) and whether they are statistically significant. There are numerous examples in the literature of unfavourable or statistically non-significant results not being published. Systematic reviews that fail to include such studies will overestimate the true effect of an intervention. Note that systematic reviews of small trials are much more susceptible to this type of bias. Because publication bias is difficult to identify of the basis of the methods provided by the authors, and may occur despite comprehensive efforts to identify all unpublished studies, a number of statistical tools exist that assess the potential for publication bias but none of them are fail-proof and work best for reviews of > 30 studies (highly unusual situation). The most common of these include the use of funnel plots, calculating a fail-safe N, and the trim and fill method. Q2. What is reasonable to pool the results? a) Was the clinical question addressed sufficiently precise? When determining whether the question addressed by the systematic review is too broad, too narrow, or reasonable, clinicians need to consider whether they would expect the treatment effect to be the same across the range of patients included. This judgement should be based on current knowledge of biology, pathophysiology, and pharmacology. It has been suggested that the best way to answer this question is to assess the homogeneity of the included studies and of the results themselves.
b) Were the studies included clinically homogenous? Here you need to consider whether you would expect the same treatment effect across the range of populations, interventions, and outcomes included in the systematic review by comparing the studies included in the pooled analysis (Table 1). c) Are the estimates of treatment effect (results) similar across studies? If the treatment effect is similar across studies then it is appropriate to pool the results. Otherwise, it is best to not pool the results or only pool across similar or homogenous studies. A simple way to answer this question is by assessing the extent of overlap of the point estimates and the confidence intervals across studies (i.e., “eyeball test” of forest plot). Note that there is some judgement involved here. d) Did authors execute a test of heterogeneity? Was the result non-significant? Statistical tests of heterogeneity assess whether the differences in results across studies (i.e., point estimates and 95% CI) are greater that than due to chance. Unfortunately, since the sample size of a systematic review is the number of individual studies included in the analysis, tests of heterogeneity tend to be underpowered (i.e., will typically yield nonsignificant results even when true heterogeneity exists because the sample size (n=number of studies meta-analyzed) is small). In other words, a non-significant result does not rule out heterogeneity. This is why the “eyeball test” mentioned above is probably the best way of evaluating study heterogeneity. Reasons for study heterogeneity include differences between patient populations, interventions, outcome measures, and methodology. e) Did they undertake a meta-regression to identify sources of heterogeneity? A meta-regression is a type of meta-analytic method used to identify variability beyond chance that is observed between studies. In other words, it can identify whether differences between studies are an important source of variation (beyond random chance). They are more powerful than global tests of heterogeneity discussed above in that they can identify individual components of studies (e.g., population, intervention, outcomes, and methodologic differences) that explain the variation in results across studies. Since the unit of analysis is individual studies, meta-regression analyses can also have limited power. Q3. Were the studies pooled of high methodologic quality? a) Did authors assess the quality/validity of the original studies? The results of a meta-analysis are only as valid as the validity of individual study results. Remember the analogy with sausage making; the sausage is only as good as the quality of its individual ingredients! Since peer review does not guarantee the validity of study results, the methodologic quality of individual studies must be assessed before pooling using the criteria discussed in CARL (i.e., randomization, concealed allocation, blinding of treatment, intention-to-treat analysis, and low losses to follow up). Note that evidence indicates that less rigorous studies (i.e., methodologically weaker) tend to overestimate the effectiveness of an intervention. b) If so, did they take study quality/validity into account in the design and/or analysis? Reviewers should apply well established validity criteria both in selecting studies for inclusion and in assessing the validity of the included studies. For example, they may restrict the analysis to high (or highest) quality studies only or undertake sensitivity analyses by removing poor quality studies from the analysis.
Q4. Were assessments of studies reproducible? a) Was study selection and data abstraction undertaken by ≼ 2 independent reviewers? The process of selecting studies to include, determining study validity, and extracting data requires judgement (i.e., somewhat subjective). As such, these critical steps are subject to human error (i.e., random errors) and bias (i.e., systematic errors). Having two or more individuals independently carrying out these different steps and comparing results minimizes the impact of these sources of error. b) If so, was interrater agreement evaluated? Reported? If there is good agreement beyond chance between two or more reviewers, then clinicians can have more confidence in the results of the systematic review because it is indicative of less subjectivity in the process. PART B: WHAT ARE THE RESULTS? Q1. What are the overall results? Interpret these the same way you would interpret the results of individual trials keeping in mind the potential impact of heterogeneity. Q2. How precise were the results? If pooled estimate is statistically significant, assess the lower boundary of the CI, otherwise (i.e., non-significant), assess the upper boundary of the CI for clinical significance. PART C: CAN I APPLY THE RESULTS TO THE CARE OF MY PATIENT(S)? Q1. Is my patient represented in any of the subgroups analyzed? If so, are the results of the subgroup valid? While the results of a subgroup analysis may be more applicable to an individual patient than the result of the “averageâ€? population across all studies, the validity of such analyses needs to be carefully evaluated given the increased possibility of type 1 error due to the use of multiple comparisons (see guidelines for the evaluation of subgroup analyses). Q2. Were all clinically important outcomes considered? While focused reviews of the evidence are more likely to provide valid results of the impact of a specific therapy on health outcomes, clinical decisions require considering other competing benefits and risks. Q3. Are the benefits worth the risks for my patient(s)? Note that systematic reviews typically do not report on the adverse effects of therapy, only benefits. Individual studies may not measure or report all adverse effects, or report them in different ways, making pooling or summarization difficult. Moreover, most individual studies are underpowered to assess the risk of serious adverse events and pooling zeros returns a zero. The latter is not the same as demonstrating absence of harms. Consequently, information on risks associated with the treatment may have to be extrapolated from individual studies Q4. Are the benefits worth the cost for my patient(s)? Costs are rarely considered in systematic reviews so this information may have to be extrapolated from individual studies.
WORKSHEET NOT INCLUDING NOTES
CRITICAL APPRAISAL OF SYSTEMATIC REVIEWS / META-ANALYSES Prepared by: Dr. Linda Lévesque, BScPhm, MSc, PhD Department of Community Health and Epidemiology, Queen’s University
PART A: ARE THE RESULTS VALID? Q1. Was the search for relevant studies detailed and exhaustive? a) Did authors search Medline, EMBASE & the Cochrane Trial registry? b) Did they check the reference list of retrieved articles? c) Did they contact experts in the field to identify unpublished studies? d) Did they undertake a quantitative evaluation of publication bias? Q2. What is reasonable to pool the results? a) Was the clinical question addressed sufficiently precise? b) Were the studies included clinically homogenous? c) Are the estimates of treatment effect (results) similar across studies? d) Did authors execute a test of heterogeneity? Was the result non-significant? e) Did they undertake a meta-regression to identify sources of heterogeneity? Q3. Were the studies pooled of high methodologic quality? a) Did authors assess the quality/validity of the original studies? b) If so, did they take study quality/validity into account in the design and/or analysis? Q4. Were assessments of studies reproducible? a) Was study selection and data abstraction undertaken by ≥ 2 independent reviewers? b) If so, was interrater agreement evaluated? Reported?
PART B: WHAT ARE THE RESULTS? Q1. What are the overall results? Q2. How precise were the results?
PART C: CAN I APPLY THE RESULTS TO THE CARE OF MY PATIENT(S)? Q1. Is my patient represented in any of the subgroups analyzed? If so, are the results of the subgroup valid? Q2. Were all clinically important outcomes considered? Q3. Are the benefits worth the risks for my patient(s)? Q4. Are the benefits worth the cost for my patient(s)?
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Dr. John Queenan - Tertiary Prevention: A comparison of patient follow-up through family physician vs. specialist care ! ! !
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Tertiary(Prevention(Session(Summary:(“Randomized(Trial(of(Long:Term(Follow:Up(for(Early:Stage( Breast(Cancer:(A(Comparison(of(Family(Physician(Versus(Specialist(Care”* (
Background(&(Current(Practice(
! Breast*cancer*is*the*most*prevalent*cancer*in*women,*due*to*its*high*incidence,*early*diagnosis,*and* greater*than*than*80%*survivorship*"*151,000*survivors*in*Canada*and*2*million*survivors*in*the*U.S.,* with*these*numbers*increasing*steadily.** ! PostFtreatment*routine*followFup*appointments*mark*the*transition*from*intensive*treatment*to* survivorship.* ! There*are*two*types*of*postFtreatment*followFup:*(1)*Usual*practice*of*followFup*by*specialists*in*cancer* clinics*or*community*practice*(the*cancer+center+(CC)*in*this*study)*and*(2)*FollowFup*by*their*family+ physician+(FP)* ! FPs*do*not*typically*play*a*formal*role*in*the*Western*world,*but*patients*often*present*first*to*their*FP,* and*many*FPs*would*prefer*a*more*active*role.** ! This*study*was*a*large,*multicenter,*randomized*controlled*trial:* o Hypothesis:*Routine*followFup*by*the*patient’s*FP*is*a*safe*and*acceptable*alternative*to* specialist*followFup*of*breast*cancer*patients.* ! Primary(outcome:*Rate*of*recurrenceFrelated*serious*clinical*events*(SCEs)* ! Secondary(outcome:*HealthFrelated*quality*of*life*(HRQL)*
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Methods(
Six*of*nine*regional*cancer*centers*in*Ontario*participated.* Patient*enrolment:*January*1997*to*June*2001*(55%*of*patients*invited*to*the*study*agreed*to*enrol).** Patients*were*followedFup*until*June*2003.* Target*population:*Women*with*earlyFstage*breast*cancer*who*had*completed*radiotherapy,*adjuvant* chemotherapy,*or*both*at*least*3*months*prior,*who*were*diseaseFfree,*and*who*were*between*9F15* months*postFdiagnosis.* ! HRQL*compared*by*using*standardized*validated*questionnaires.** ! ! ! !
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Results(&(Discussion( ! ! ! ! ! ! ! ! !
968*women*enrolled:*485*into*the*CC*group*and*483*into*the*FP*group.* *“The*two*groups*were*reasonably*well*balanced*for*baseline*characteristics”.** Average*age:*61*years.* This*study*showed*that:*(1)*SCEs*are*extremely*rare*(35*in*3,240*patientFyears)*and*that*(2)*SCEs*are*with* equal*frequency*regardless*of*the*two*followFup*care*types.* FP*followFup*was*not*found*to*be*worse*than*CC*followFup*with*respect*to*SCEs.** There*was*no*clinically*significant*difference*between*the*groups*with*respect*to*HRQL.** The*study*is*generalizable*to*most*breast*cancer*survivors:*~70%*of*participants*had*nodeFnegative* breast*cancer,*consistent*with*the*general*population.* FP*followFup*is*likely*to*be*more*convenient*for*patients,*and*possibly*less*costly.* To*use*FP*care,*investigating*methods*to*disseminate*new*knowledge*to*FPs*are*essential.*
* Guiding(Questions* ! What*do*you*think*are*the*pros(and(cons*of*family*physician*followFup*care*for*breast*cancer?* ! 83%*of*FPs*in*this*study*agreed*to*provide*followFup*care.*Do*you*think*that*the*willingness*of*FPs*to* take*on*this*additional*level*of*care*is*generalizable*to*the*FP*population*as*a*whole*in*Ontario?** Grunfeld,*E.,*Levine,*M.*N.,*Julian,*J.*A.,*Coyle,*D.,…,*Whelan,*T.*(2006).*Randomized*Trial*of*LongFTerm*FollowFUp* for*EarlyFStage*Breast*Cancer:*A*Comparison*of*Family*Physician*Versus*Specialist*Care.*Journal(of( Clinical(Oncology,(24(6):*848F855.*DOI:*10.1200/JCO.2005.03.2235
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Dr. Jason Pennington & Ms. Usman Aslam Aboriginal Cancer Strategies: Provincial and Regional Perspectives !
The$Aboriginal$Cancer$Strategy$III$ What is the Aboriginal Cancer Strategy? Three peoples (First Nation, Inuit and Me’tis and other Aboriginal partners) coming together with Cancer Care Ontario to work to address cancer issues and create unique and diverse solutions for healing and health. Vision: To improve the performance of the cancer system with and for First Nations, Inuit and Métis peoples in Ontario in a way that honours the Aboriginal Path of Well-being. Facts • People with any Aboriginal origins have been found to have higher age standardized mortality rates than people with no Aboriginal ancestry (Marrett and Chaudhry 2003; Wilkins 2008). • Cancer incidence rates for major cancers are increasing more rapidly among First Nations people, and cancer survival is worse in this population compared with other Ontarians. • Rising burden of cancer among Aboriginal peoples has been attributed at least in part to the higher prevalence of several modifiable risk factors, such as smoking, poor diet and obesity. What do you think contributes to these disparities? How is the Aboriginal Cancer Strategy working to decrease these disparities? • Focusing risk reduction efforts on individual behaviour is unlikely to have a significant and lasting impact on reducing cancer risk and incidence cancer in aboriginal communities without also putting in place complementary system-level initiatives that target the broader determinants of health through improved public health policy and community programming Strategic Priority 1: Building Productive Relationships The Path: Health in balance Objectives—by 2019 • Create accountability for ACS III between Cancer Care Ontario and governance bodies of Aboriginal groups • Support capacity building of RCPs to lead, successfully engage local First Nations, Inuit and Métis groups and implement cancer control initiatives as guided through Regional Aboriginal Cancer Plans. • Help First Nations, Inuit and Métis people with cancer navigate cancer services in and outside of the hospital in a way that honours the Aboriginal Path of Well-being and ensure that patients have access to high-quality, culturally appropriate care throughout their cancer journey. • Work with First Nations and Inuit leaders and Health Committees to help address programming and service gaps and extend the Non-Insured Health Benefits (NIHB) policy to include cancer control needs. • Build Cancer Care Ontario’s capacity for planning appropriate services and guidelines that take into consideration the unique needs of the Aboriginal population. • Strengthen energy for and sustain outcomes of relationship-building by defining and measuring respect and trust. Strategic Priority 2: Research & Surveillance The Path: Understand root causes Achievements from ACS II Objectives—by 2019 • Identify, access, and analyze comprehensive and high-quality surveillance data specific to First Nations, Inuit and Métis groups. • Develop research to address relevant questions regarding risk factors, screening and/or cancer burden profiles among First Nations, Inuit and Métis peoples • Through effective dissemination and education, support First Nations, Inuit and Métis communities in understanding and acting on implications of surveillance and research data in terms of policy and program development. • Build system capacity around an Aboriginal cancer research agenda, starting with enhanced research capacity at CCO Strategic Priority 3: Prevention The Path: Wellness— emotional and spiritual Objectives—by 2019 • Develop an explicit, trackable, relevant model for increasing community tobacco-wise awareness & changing behaviour • Demonstrate effective partnerships and collaborations with groups and organizations that are part of the ATPT, and define clear, complementary roles.
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Further establish metrics on data quality, methods, analysis, dissemination and uptake. Develop better information on the quantity and quality of frontline health promotion behaviours. Complete an assessment of existing tobacco policies (both formal and informal) in communities; assess where community and health leaders see future opportunities and determine additional informational needs required. Develop evidence to inform success for First Nations, Inuit and Métis communities in addressing commercial tobacco cessation that is both sensitive and generalizable across the diverse social, political, cultural and environmental contexts of Aboriginal communities. Establish evidence that reflects the unique issues Aboriginal people face and develop recommendations to address modifiable risk factors associated with preventing and managing chronic diseases
Strategic Priority 4: Screening The Path: Active choice Objectives—by 2019 • Expand the reach and understanding of SARs to support healthcare providers in communities in cancer screening invites and follow-up. • Explore data linkage opportunities to further develop community-based cancer screening reports and surveillance studies. • Develop evidence of barriers to First Nations, Inuit and Métis cancer screening in existing policies and processes, and identify levers for change that will improve cancer screening participation. • Support evidence-informed assessment of the options for, investments in and benefits of sending invitations to eligible First Nations, Inuit and Métis individuals for cancer screening and follow-up. • Support new and emerging opportunities for First Nations, Inuit and Métis communities to access timely cancer screening and increase screening participation rates. Strategic Priority 5: Palliative and End-of-Life Care The Path: Holistic approach Objectives—by 2019 • Develop a process that captures and embeds the First Nations, Inuit and Métis perspective and experience in the cancer system and program development to improve access and remove barriers to high-quality care and positive patient experience outcomes. • Evaluate whether First Nations, Inuit and Métis people with cancer and their families receive, have access to, understand and apply relevant palliative care information. • Demonstrate increased use of Edmonton Symptom Assessment System (ESAS), to facilitate pain and symptom management for First Nation, Inuit and Métis patients. • Establish culturally appropriate tools and methods for collecting Patient Reported Outcome Measures (PROMs) and Patient Reported Experience Measures (PREMs) for First Nation, Inuit and Métis peoples, and ensure that PROMs and PREMs inform conversations and treatment decisions between patients and clinicians. • Support user-led Learning Essential Approaches to Palliative and End-of-Life Care (LEAP) curriculum development. • Conduct collaborative assessments of palliative care programming and services to identify current state, future potential roles, and barriers and enablers. Strategic Priority 6: Education The Path: Joint and personal responsibility Objectives—by 2019 • Support cultural safety across the cancer system by ensuring that e-modules are made available to and completed by Aboriginal-serving healthcare providers • Gather evidence on the impact of the e-modules on professional competency in delivering culturally safe cancer care. • Develop robust evidence regarding who and how many people access the ATP website, and why. • Develop evidence on the comprehensiveness of information, effective distribution and utility of “Cancer 101”, smoking cessation brochures, “Tools for the Journey” palliative care resources, and cancer screening fact sheets. • Establish a framework to identify, engage and measure key target audiences for ACS III (e.g., First Nations, Inuit and Métis communities and people with cancer, primary care providers, Cancer Care Ontario staff, RCPs). Thinking Points / Guiding Questions What role will different health professionals have in helping to achieve these objectives? Do you feel that these objectives are attainable by 2019? Why or why not?