Interventions for raising breast cancer awareness in women
Abstract
This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:
To assess the effectiveness of interventions for raising breast cancer awareness in women.
Background
Description of the condition
Although death rates are declining (Siegal 2013), breast cancer continues to be the most commonly diagnosed cancer in women globally (Bray 2012). According to World Health Organization (WHO) Global Health Estimates, worldwide over 508,000 women are estimated to have died in 2011 due to breast cancer (WHO 2014). Early diagnosis of breast cancer is linked to more favourable outcomes and longer survival (Richards 1999a; Richards 1999b). While screening mammography is effective in detecting some breast cancers, accuracy is dependent on breast density (Carney 2003). Additionally, many breast tumours are initially detected by women themselves (as opposed to by mammographic screening) (Cancer Research UK 2014). However, some women postpone presenting to a healthcare professional (HCP) on finding a breast symptom. In an attempt to develop consistency in definitions and approaches used in early cancer‐diagnosis research, Weller 2012 developed the "Aarhus checklist" as a resource for researchers. In their paper outlining this checklist, the "patient interval" (Olesen 2009) is described as the (i) "time taken to interpret bodily changes/symptoms" i.e. "appraisal interval" and (ii) the "time taken to act upon those interpretations and seek help" i.e. the "help‐seeking interval" (Weller 2012). To date, in relation to breast symptoms, this "patient interval" varies from one month, to up to three months and greater than three months (Arndt 2002; Forbes 2012; Jones 2010; Meechan 2002; O'Mahony 2009; O'Mahony 2011; O'Mahony 2013). Postponement of help seeking (previously referred to as delay) is associated in particular with women's lack of knowledge of non‐lump breast symptoms (e.g. nipple changes; O'Mahony 2013). This is a worrying situation given the increased emphasis on prompt presentation of breast symptoms and the associated link with better healthcare outcomes for women who are diagnosed with breast cancer earlier in the disease trajectory.
Traditionally breast cancer screening has included breast self‐examination (BSE), clinical breast examination and screening mammography (MacBride 2012). Screening mammography is described as "the most widely used and best available tool for detecting breast cancer" (MacBride 2012). However, the efficacy of screening programs is dependent on women's participation (Chan 2007). Since many women will present with a palpable breast mass (MacBride 2012) it is important that they have the knowledge, skills and confidence necessary to detect and seek help for breast cancer symptoms.
BSE is described as "a regular, repetitive monthly palpation to a rigorous set method performed by the woman at the same time each month" (Thornton 2008) using a method that has been formally taught to women (MacBride 2012). While BSE continues to be advocated for early detection of breast symptoms (American Cancer Society 2014), a Cochrane Review reported lack of evidence to support the use of breast screening by BSE or clinical examination of breasts by a HCP in improving breast cancer mortality rates (Kösters 2003). Nonetheless, the review highlighted the need for women to be able to identify breast changes and seek prompt medical advice should they discover changes that may be breast cancer. This is further reiterated by the WHO 2014 which recommends BSE as a means of "raising awareness amongst women at risk" of breast cancer. Additionally, the practice of BSE is incorporated into some breast health awareness interventions (Chan 2007; Kharboush 2011) and to breast health promoting strategies (Byrne 2009). Alternatively, the term "breast checking" has been used as part of a measure of breast cancer awareness (Forbes 2011; Forbes 2012; Linsell 2009) where women were asked to report on how frequently they checked their breasts.
Currently the term "breast awareness" is cited in relation to breast cancer screening and early detection of breast cancer (American Cancer Society 2014; IARC 2014; National Comprehensive Cancer Network 2013; NICE 2013). Furthermore, a recent editorial in the Breast Journal (MacBride 2012) highlighted "a paradigm shift" from BSE to breast awareness, advocating that breast awareness become part of general breast health education. Breast awareness involves women having confidence to "look at and feel" their breasts so that they know what is normal for their own body and what changes to look and feel for (Irish Cancer Society 2013; National Comprehensive Cancer Network 2013; NHS Breast Cancer Screening Programme 2013). In addition, breast awareness requires that women have an understanding of the implications of breast changes and consult with their healthcare provider promptly (MacBride 2012). Therefore, the concepts of "breast awareness" and "breast cancer awareness" are inextricably linked. In addition BSE and, more recently, breast checking are referred to as the behavioural components of each.
Whilst breast awareness is advocated globally, evidence suggests that women generally are not breast aware (Kharboush 2011). Furthermore, it is suggested that public education about cancer symptoms and the value of early detection could enhance early presentation and improve cancer outcomes (Robb 2009). Thus, the need for HCPs to increase awareness of breast cancer symptoms in women is crucial. In the United Kingdom, the promoting early presentation (PEP) intervention was developed providing older women (who are at much higher risk of developing breast cancer) with knowledge, skills, confidence and motivation to present early with breast cancer symptoms (Forbes 2011;Forbes 2012;Linsell 2009). However, due to the earlier median age of diagnosis for breast cancer compared with other major cancers, it is suggested that women have a slightly higher probability of developing cancer before age 60 years (Siegal 2011). Currently, in Ireland 50% of women who are newly diagnosed with breast cancer are under 60 years of age (mean age of diagnosis is 59.6 years; National Cancer Registry Ireland 2012). In relation to the effects of age on delayed diagnosis and treatment of breast cancer, a recent American study (Partridge 2012) concluded that age is not a predictor of delayed diagnosis of breast cancer. Nonetheless, the researchers suggest the need to enhance symptom recognition amongst women of all ages, in particular younger women in order to reduce the effects of delayed diagnosis. In addition, the need to reduce the health and economic burden of a breast cancer diagnosis in younger women (aged 20 to 49 years) in the United States of America has recently been highlighted (Ekwueme 2014). Thus, increasing breast awareness in women is necessary if these targets are to be met. A systematic review of interventions to promote cancer awareness and early presentation found limited evidence of the effectiveness of such interventions (Austoker 2009). In addition, there is lack of evidence of the impact of increased breast cancer awareness on early detection of breast cancer. Therefore, a review to assess the effectiveness of interventions for raising breast cancer awareness in women is warranted.
Description of the intervention
For this Cochrane Review, we will consider any intervention designed to raise awareness of breast cancer. We will include the interventions of information or education, or both, specific to: (i) breast cancer (potential breast cancer symptoms/changes; (ii) breast awareness (i.e. women having the confidence to look at and feel (palpate) their breasts so that they know what is normal for their own body and what changes to look and feel for). We will extract details relating to the (i) format (written, verbal, online); (ii) timing (number of sessions; time between sessions and duration of follow‐up period); (iii) method of delivery (one‐to‐one/group/mass media campaign(s); (iv) content; and (vi) theoretical underpinnings of each intervention.
How the intervention might work
The development of complex health related interventions requires a clear theoretical basis (Campbell 2007; Craig 2008). Understanding of the theoretical perspectives underpinning such interventions is critical if their effectiveness and usefulness in practice are to be evaluated (Michie 2012). Therefore, clarity surrounding the factors linked to breast cancer awareness and initiation of behavioural change is critical in terms of designing interventions to raise breast cancer awareness in women.
Currently, information and education relating to the promotion of breast cancer awareness are either specifically targeted at "high risk" individuals who have a greater risk of developing breast cancer or they may be directed towards women in general. However, there is a need to develop more innovative strategies to promote breast health awareness and early detection of breast cancer in women (Byrne 2009). It is suggested that early diagnosis of breast cancer (enhanced by raising women's breast cancer awareness) could lead to decreased morbidity or mortality rates, or both, of women (Richards 2009).
Why it is important to do this review
Increasing women's awareness of breast cancer symptoms aims to increase the number of women who present early to a HCP with symptoms. Early presentation to a HCP has potential to increase early detection of breast cancer resulting in early treatment and enhanced survival rates for women (Richards 2009). Conversely, as highlighted by Kösters 2003, increased BSE may lead to unnecessary anxiety, medical consultations and costly follow‐up screening procedures for women. It could be argued that increasing breast cancer awareness could have similar effects. However, the benefits of early detection and prompt presentation of symptoms could outweigh these.
It is apparent that there has been no systematic review undertaken on the effects of educational interventions for raising breast cancer awareness in women. Such a review would provide clarity in relation to these interventions and on outcomes for women who are subsequently diagnosed with breast cancer. Thus, a systematic review to determine the impact of interventions for raising breast cancer awareness in women would benefit HCPs globally in their efforts to reduce breast cancer burden through its early detection (Bray 2012), diagnosis and treatment. Data from the review will determine the impact of increased breast cancer awareness on earlier detection, stage of cancer at diagnosis and survival outcomes. This knowledge could help to direct future strategies around the promotion of breast cancer awareness and contribute to the global effort to reduce mortality and morbidity due to breast cancer.
Objectives
To assess the effectiveness of interventions for raising breast cancer awareness in women.
Methods
Criteria for considering studies for this review
Types of studies
We will include randomised controlled trials (RCTs) and cluster RCTs of interventions for raising breast cancer awareness in women. In addition, we will consider non‐randomised studies provided they have (i) a control group and (ii) pre‐ and post‐test estimates of the effectiveness of the intervention. Studies should describe levels of potential confounders (e.g. age; socioeconomic status; education level, ethnicity, family history of breast cancer, previous benign disease) in the intervention and non‐intervention group and whether or not researchers adjusted for these.
Types of participants
Women (with or without a previous breast cancer diagnosis) specifically recruited to receive an intervention to raise breast cancer awareness will be eligible for inclusion. We will exclude interventions aimed at raising breast cancer awareness amongst HCPs.
Types of interventions
Group or individual educational interventions specifically focusing on raising breast cancer awareness in women will be eligible for inclusion. Interventions should promote breast cancer awareness for women through the provision of information on: (i) breast cancer symptoms and (ii) breast awareness (i.e. women having the confidence to look at and feel (palpate) their breasts so that they know what is normal for their own body and what changes to look and feel for) (Forbes 2011; Forbes 2012; Linsell 2009).
The intervention will take place in any setting i.e. clinical/online/community and may involve one single session or a number of sessions. Interventions may be provided in a combination of various formats including written brochures, video/audio tape, online or media campaigns.
We will exclude studies in which the intervention forms part of a multi‐component intervention in order to avoid confounding effects (i.e. interventions associated with knowledge of other cancers, other chronic illnesses and general lifestyle behaviours). Also, we will exclude interventions promoting uptake of breast cancer screening exclusively.
Standard care or no intervention will be eligible as the comparator.
Types of outcome measures
Primary outcomes
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Women's knowledge of breast cancer symptoms. This will be based on patient reported knowledge and awareness scores from validated scales e.g. Breast Cancer Awareness Measure: BCAM (Linsell 2010). In addition, we will use single measures of knowledge or awareness where reported.
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Measure of confidence to check breasts i.e. engagement in self‐care behaviours relating to breast awareness (i.e. women looking at and feeling/palpating their breasts so that they know what is normal for their own body and what changes to look and feel for. This will be apparent in data reported by women relating to their engagement in these self‐care behaviours at specific time frames.
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Measures of women's motivation to check their breasts ‐ as outlined above (if available).
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Measures of confidence to seek help when breast cancer symptoms are noticed (if available).
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Measure of time from breast cancer symptom being noticed to presentation to a HCP (time to event data) indicating postponed or prompt help‐seeking behaviour (if available).
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Measure of women's intentions to seek help in the event of noticing a breast cancer symptom and their perceptions of barriers to help seeking (if available).
Secondary outcomes
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Quality of life (classified by scales used by the trial authors) or any measure of health status (i.e. physical, psychological, social, spiritual, existential).
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Adverse effects of receiving the intervention on breast cancer awareness or adverse outcomes related to false positive findings of symptoms (such as increased anxiety) assessed by any validated self‐report scale, or both.
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Stage of breast cancer at diagnosis i.e. tumour, node, metastases status (where reported).
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Survival estimates: i.e. measured either from time of intervention or time of breast cancer diagnosis (where reported).
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Breast cancer‐specific mortality and all‐cause mortality (where reported).
Search methods for identification of studies
Electronic searches
We will search the following databases:
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the Cochrane Breast Cancer Group's (CBCG's) Specialised Register. Details of search strategies used by the CBCG for the identification of studies and procedures to code references are outlined in the CBCG's module (http://onlinelibrary.wiley.com/o/cochrane/clabout/articles/BREASTCA/frame.html). We will extract studies coded with the key words "breast cancer", "breast cancer awareness", "breast awareness", "health education", "health promotion", "educational program", and "educational intervention" and consider these studies for inclusion. CENTRAL (latest issue). See Appendix 1.
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MEDLINE (via OvidSP). For RCTs, a date limit will be applied (from 2008 onwards) to coincide with those years where references have not been uploaded into the CBCG Specialised Register. See Appendix 2.
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EMBASE (via EMBASE.com). For RCTs, a date limit will be applied (from 2008 onwards) to coincide with those years where references have not been uploaded into the CBCG Specialised Register. See Appendix 3.
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The WHO International Clinical Trials Registry Platform (ICTRP) search portal (http://apps.who.int/trialsearch/Default.aspx) for all prospectively registered and ongoing trials. See Appendix 4.
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Clinicaltrials.gov (http://clinicaltrials.gov/). See Appendix 5.
Searching other resources
Bibliographic searching
We will try to identify further studies from reference lists of identified relevant studies or reviews. A copy of the full article for each reference reporting a potentially eligible study will be obtained. Where this is not possible, we will attempt to contact trial authors for additional information. Also, we will perform a forwards citation search as appropriate.
Grey literature
We will include grey literature (i.e. unpublished data such as reports, conference proceedings/abstracts, and doctoral theses) to enable us to retrieve as much information as possible and minimise the effects of publication bias.
Data collection and analysis
Selection of studies
Two review authors (MOM and JH) will independently assess the titles and abstracts of each identified study for inclusion in the review and examine compliance of identified studies with the eligibility criteria. Following this initial evaluation, we will retrieve the full text articles of all potentially relevant publications. We will resolve any disagreements regarding eligibility of studies by consulting a third author (MC). Excluded studies will be recorded in the 'Characteristics of excluded studies' section. We will translate any studies reported in a language other than English as necessary.
Data extraction and management
Two review authors (MOM and JH) will extract data from all relevant studies using a data extraction form.
Information recorded will include:
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Study details: author, date, country of origin.
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Participants: socio‐demographics (age; socio‐economic status; education level, ethnicity); breast cancer history (previous or family history, or both); number receiving intervention; number receiving usual care.
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Methods: study aim, design, total study duration.
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Intervention details: content, format, timing (already outlined), method of delivery and theoretical underpinnings (if any).
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Outcomes: extraction of all relevant findings related to primary and secondary outcomes as specified previously.
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Withdrawals, length and method of follow–up and the number of participants followed up.
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Miscellaneous issues.
For non‐randomised studies, we will record the following information:
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Methods used to control for confounders.
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Adjusted and unadjusted outcome measures.
We will resolve any disagreements regarding extraction of quantitative data by consulting a third author (MC). If necessary, we will seek additional data or information from the original trial authors. Where we retrieve studies with more than one publication, our decisions regarding which version to include will depend on consultation with the original trial authors.
Assessment of risk of bias in included studies
Two review authors (MOM and JH) will independently assess the risk of bias of included studies using the Cochrane 'Risk of bias' tool (Higgins 2011), the Cochrane EPOC Group's 'Risk of bias' criteria (Cochrane EPOC Group 2013) and recommendations by Norris 2013. In addition, we will take guidance from Chapter 13 of Higgins 2011. We will consider the six bias domains of: selection bias; performance bias; detection bias; attrition bias; reporting bias; and other potential sources of bias. We will assign each risk of bias domain a judgement of "high", "low" or "unclear" risk of bias. Where we cannot reach consensus, we will consult a third review author (MC). If necessary, we will contact the original trial authors to seek further clarification of methods used. We will summarise the results using both a 'Risk of bias' graph and a 'Risk of bias' summary. Key questions addressing each bias criterion are outlined below.
Selection bias
Was the allocation sequence adequately generated?
We will score:
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"Low risk" if a random component in the sequence generation process is described (e.g. Referring to a random number table).
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"High risk" when a non‐random method is used (e.g. performed by date of admission). Non‐randomised studies should be scored "high risk".
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"Unclear risk" if not specified in the paper (Cochrane EPOC Group 2013).
Was the allocation adequately concealed?
We will score:
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"Low risk" if participants and investigators enrolling participants could not foresee assignment (e.g. a centralised randomisation scheme, an on‐site computer system or sealed opaque envelopes were used) (Higgins 2011, Section 8.14; Cochrane EPOC Group 2013).
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"High risk" if participants and investigators enrolling participants could foresee assignment. Also non‐randomised studies should be scored "high risk".
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"Unclear risk" if not specified in the paper (Higgins 2011, Section 8.14; Cochrane EPOC Group 2013).
For non‐randomised studies we will also consider the following questions:
Were baseline outcome measurements similar?
We will score:
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"Low risk" if performance or patient outcomes were measured prior to the intervention, and no important differences were present across study groups.
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"High risk" if important differences were present and not adjusted for in the analysis.
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"Unclear risk" if not specified in the paper (Cochrane EPOC Group 2013).
Were baseline characteristics similar?
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"Low risk" if baseline characteristics of the study and control providers are reported and similar.
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"Unclear risk" if it is not clear in the paper (e.g. characteristics were mentioned in text but no data were presented).
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"High risk" if there is no report of characteristics in text or tables or if there are differences between control and intervention providers (Cochrane EPOC Group 2013).
Was there adequate adjusting for confounding?
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"Low risk" if appropriate methods were used to adjust for confounding.
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"Unclear risk" if the methods used to adjust for confounding were not reported.
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"High risk" if potential confounding from the following variables were not addressed: age; socio‐economic status; education level, ethnicity, family history of breast cancer, previous benign disease (Higgins 2011, Sections 13.21 to 13.23; Norris 2013).
Performance/detection bias
Was knowledge of the allocated interventions adequately prevented during the study?
We will score:
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"Low risk" if the trial authors state explicitly that the primary outcome variables were assessed blindly or the outcomes are objective, e.g. time to event data (prompt or delayed help‐seeking behaviour, i.e. presentation of breast symptoms to HCP).
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"High risk" if the outcomes were not assessed blindly.
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"Unclear risk" if not specified in the paper (Cochrane EPOC Group 2013).
Attrition bias
Were incomplete outcome data adequately addressed?
We will score:
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"Low risk" if missing outcome measures were unlikely to bias the results (e.g. reasons for missing outcome data are unlikely to be related to true outcome, missing outcomes data are balanced in numbers across intervention groups with similar reasons for missing data across groups or missing data were imputed using appropriate methods) (Higgins 2011, Section 8.16).
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"High risk" if missing outcome data was likely to bias the results.
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"Unclear risk" if it is not specified in the paper (Cochrane EPOC Group 2013).
Reporting bias
Were reports of the study free from selective outcome reporting?
We will score:
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"Low risk" if there is no evidence that outcomes were selectively reported (e.g. pre–specified outcomes are available in the study protocol or all relevant outcomes in the methods section are reported in the results section).
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"High risk" if some pre‐specified outcomes are subsequently omitted from the results.
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"Unclear risk" if not specified in the paper (Cochrane EPOC Group 2013; Higgins 2011, Section 8.17).
Was the study free from selective analysis reporting?
We will score:
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"Low risk" for each outcome if there is no evidence that analyses were selectively reported (e.g. analyses were outlined in the methods section of the protocol or paper).
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"High risk" if there is evidence of selective analysis reporting (e.g. multiple adjusted analyses have been carried out and only one reported or "extreme" cut points have been have been used for creating categorical outcomes).
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"Unclear" if not specified in the paper (Cochrane EPOC Group 2013; Norris 2013).
Measures of treatment effect
We will use Review Manager 2014 to perform all analyses. Final decisions regarding if and how to combine outcomes will depend on how data are reported in the included studies. We will consult Section 9.2 "Types of data and effect measures" of Higgins 2011 to guide our decisions.
The data could be:
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Dichotomous (yes/no) (i.e. increased knowledge/awareness of breast cancer symptoms; increased confidence to engage in self‐care behaviours relating to breast cancer awareness, such as increased confidence and motivation to palpate breasts; increased confidence to seek help; increased intention to seek help/time to event, such as early presentation of potential breast cancer symptoms; mortality and presence of adverse effect of the intervention).
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Continuous (e.g. changes in anxiety scales as a result of the intervention).
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Ordinal (e.g. tumour classification i.e. stage/size; categories on a quality of life scale such as mild, moderate or severe).
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Nominal: perceptions of barriers to seeking help.
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Time‐to‐event: breast cancer‐specific mortality and survival estimates.
We will estimate the effect measurement for dichotomous outcomes using the odds ratio as the summary statistic. Ordinal data will be analysed either as continuous data (tumour classification i.e. stage/size) or dichotomous data (cancer type: in situ yes/no or invasive yes/no). In the case of quality of life, we will analyse data as continuous or dichotomous depending on how trial authors report data in the included studies.
We will determine the effect measurement for continuous data (changes in anxiety levels/decreased quality of life/economic factors) using the mean difference (MD) and standard deviation (when outcomes are measured using the same scales). Where anxiety and quality of life are measured using different scales, we will calculate the standardised mean difference (SMD) where appropriate.
Regarding survival (time to event) data, we will use hazard ratios as the summary statistic. We will use 95% confidence intervals (CIs) throughout the review.
Unit of analysis issues
Unit of analysis regarding women's breast cancer awareness over specific time frames have been categorised as short, medium and long term i.e. six months, 12 months and two years respectively (Forbes 2011; Linsell 2009). As far as possible, we will identify periods of follow‐up (post‐intervention) in a similar fashion to reflect the effects of interventions on raising breast cancer awareness within short (≤ one month), medium (≤ one year) and long term (≤ two year) time intervals.
Dealing with missing data
We will attempt to seek Information on missing data by contacting the trial authors. If unsuccessful, we will present the data narratively and discuss it in the main text of the review.
Assessment of heterogeneity
We will assess inconsistency in study results i.e. statistical heterogeneity (due to clinical or methodological diversity) by reviewing the CIs for results of individual studies (generally depicted graphically using horizontal lines where poor overlap of results indicates the presence of statistical heterogeneity) (Higgins 2011). We will quantify inconsistency across studies using the I2 statistic which describes "the percentage of variability in effect estimates that is due to heterogeneity rather than sampling error (chance)" (Higgins 2011). It is suggested that a result greater than 50% indicates substantial heterogeneity (Higgins 2011).
Assessment of reporting biases
Where reporting bias is identified, we will contact the trial authors to provide information on missing data. Alternatively, if this is not possible and we suspect bias, we will determine the impact of including such studies by testing for funnel plot asymmetry (as recommended in Section 10.4.3.1 of Higgins 2011). We will include outcomes and implications of results in the Discussion section, if appropriate.
Data synthesis
Using Review Manager 2014 we will analyse the data. One review author (MOM) will analyse the extracted data and report the findings (as outlined in Higgins 2011).
Initially, we will use a random‐effects model. However, where we detect homogeneity across studies, we will use a fixed‐effect model for meta‐analysis (Higgins 2011). Random‐effects pooled estimates will be obtained as follows: for dichotomous outcomes, we will pool odds ratios using the DerSimonian and Laird random‐effects method (DerSimonian 1986; Higgins 2011). Regarding continuous outcomes, we will pool data using the inverse variance random‐effects method. We will obtain pooled estimates of time‐to‐event outcomes using the random‐effects inverse variance method. Fixed effect pooled estimates will be obtained using the Mantel‐Haenszel method for dichotomous outcomes and inverse‐variance method for continuous outcomes. Regarding time to event data, we will use the inverse variance method to pool estimates of the log(hazard ratio) (Higgins 2011).
Where it is not reasonable to pool estimates, we will provide a narrative account of the results of individual included studies. In the event that cluster‐RCTs meet our inclusion criteria, we will analyse the data based on Section 16.3 of Higgins 2011. We will prepare a 'Summary of findings' table using GRADEpro software (as recommended in Chapter 1 of Higgins 2011).
Subgroup analysis and investigation of heterogeneity
We will perform subgroup analysis as necessary. This may involve analysis of subsets of participants (determined by age groups; socio‐economic factors; cultural issues; previous history of breast cancer); study details (geographical location); mode of delivery of intervention (face‐to‐face/online/one‐to‐one or group session); and time point at which the outcome was assessed (i.e. ≤ one month or ≤ one year or ≤ two years) post intervention.
Sensitivity analysis
We will perform sensitivity analysis to assess the robustness of the review. Also, we will repeat the analysis excluding studies of low methodological quality. The results of sensitivity analyses will be reported in a summary table.
