Shared Decision-Making and Short-Course Radiotherapy for Operable Rectal Adenocarcinoma: A Patient's Right to Choose.

BACKGROUND: As new treatment options for colorectal cancer (CRC) emerge, physicians and WOC nurses must be prepared to assist patients to choose care that meets their needs and preferences. A patient with T2N0M0 rectal adenocarcinoma was offered the US current standard of practice; he was not offered alternative treatment options. This case study emphasizes the need to ensure patients are offered all reasonable options for treatment. Shared decision-making is a process that helps patients actively participate in their heath choices rather than exclusively relying on the judgment of a health care provider. CASE: Mr J was a 70-year-old man with operable CRC who sought care at a health care facility in his community. He was offered a single option, based on standard of care for this tumor stage: long-course neoadjuvant chemoradiotherapy followed by surgery and additional chemotherapy. After seeking a second opinion at a cancer care center in another state, Mr J chose to undergo a viable alternative treatment option (short-course radiotherapy, followed by surgery, with chemotherapy contingent on his nodal status post-surgery). No nodal involvement was found post- surgery (T2N0M0) enabling him to avoid postoperative chemotherapy. CONCLUSIONS: This case illustrates the need for all health care providers and carers to regularly engage in shared decision-making when choosing among treatment options. In this case, short-course radiotherapy offered Mr J a shorter duration of treatment and avoided the risk for adverse side effects associated with chemotherapy, resulting in improved health-related quality of life. Initial omission to disclose all treatment options to Mr J may have reflected the preferences of the surgeon, institutional financial pressures, or discomfort with shared decision-making, but it failed to provide him with full range of options, given his diagnosis and tumor stage. All members of the patient's care team, including the WOC nurse, play a pivotal role in ensuring transparency in medical care, including advocating for shared decision-making where patients are made aware of all viable treatments, followed by supporting the patient as they reach a decision.

Ovarian suppression in combination endocrine adjuvant therapy in premenopausal women with early breast cancer.

PURPOSE: The benefits of adding ovarian suppression to either tamoxifen or aromatase inhibitors as adjuvant breast cancer therapy in premenopausal women are controversial. Therefore, we performed a systematic literature review and meta-analysis of relevant randomized trials. METHODS: We identified and combined four qualifying trials reporting disease-free survival (DFS) and overall survival (OS) using meta-analysis. RESULTS: Combining ABCSG-12, SOFT, and TEXT studies, there were 65 fewer DFS events (HR 0.89, 95% CI 0.57-1.39) but 30 more deaths for ovarian suppression plus aromatase inhibitor compared to ovarian suppression plus tamoxifen (HR 1.31, 95% CI 0.93-1.84, P = 0.12, τ = 0.03, heterogeneity, P = 0.18). DFS and OS were more concordant for combined SOFT and E-3193 findings; for ovarian suppression plus tamoxifen compared to tamoxifen alone, there were 24 fewer DFS events (HR 0.83, 95% CI 0.67-1.07, P = 0.09, τ 2 = 0) and 14 fewer deaths (HR 0.76, 95% CI 0.53-1.07). The SOFT Estrogen Substudy demonstrated inconsistent estrogen suppression with combined ovarian suppression and aromatase inhibitor. CONCLUSION: Given the discordance between DFS and OS and inconsistent estrogen suppression with ovarian suppression plus aromatase inhibitor, adding aromatase inhibitor to ovarian suppression as adjuvant therapy in premenopausal women is premature.

Decision aids for people facing health treatment or screening decisions.

BACKGROUND: Decision aids are intended to help people participate in decisions that involve weighing the benefits and harms of treatment options often with scientific uncertainty. OBJECTIVES: To assess the effects of decision aids for people facing treatment or screening decisions. SEARCH METHODS: For this update, we searched from 2009 to June 2012 in MEDLINE; CENTRAL; EMBASE; PsycINFO; and grey literature. Cumulatively, we have searched each database since its start date including CINAHL (to September 2008). SELECTION CRITERIA: We included published randomized controlled trials of decision aids, which are interventions designed to support patients' decision making by making explicit the decision, providing information about treatment or screening options and their associated outcomes, compared to usual care and/or alternative interventions. We excluded studies of participants making hypothetical decisions. DATA COLLECTION AND ANALYSIS: Two review authors independently screened citations for inclusion, extracted data, and assessed risk of bias. The primary outcomes, based on the International Patient Decision Aid Standards (IPDAS), were:A) 'choice made' attributes;B) 'decision-making process' attributes.Secondary outcomes were behavioral, health, and health-system effects. We pooled results using mean differences (MD) and relative risks (RR), applying a random-effects model. MAIN RESULTS: This update includes 33 new studies for a total of 115 studies involving 34,444 participants. For risk of bias, selective outcome reporting and blinding of participants and personnel were mostly rated as unclear due to inadequate reporting. Based on 7 items, 8 of 115 studies had high risk of bias for 1 or 2 items each.Of 115 included studies, 88 (76.5%) used at least one of the IPDAS effectiveness criteria: A) 'choice made' attributes criteria: knowledge scores (76 studies); accurate risk perceptions (25 studies); and informed value-based choice (20 studies); and B) 'decision-making process' attributes criteria: feeling informed (34 studies) and feeling clear about values (29 studies).A) Criteria involving 'choice made' attributes:Compared to usual care, decision aids increased knowledge (MD 13.34 out of 100; 95% confidence interval (CI) 11.17 to 15.51; n = 42). When more detailed decision aids were compared to simple decision aids, the relative improvement in knowledge was significant (MD 5.52 out of 100; 95% CI 3.90 to 7.15; n = 19). Exposure to a decision aid with expressed probabilities resulted in a higher proportion of people with accurate risk perceptions (RR 1.82; 95% CI 1.52 to 2.16; n = 19). Exposure to a decision aid with explicit values clarification resulted in a higher proportion of patients choosing an option congruent with their values (RR 1.51; 95% CI 1.17 to 1.96; n = 13).B) Criteria involving 'decision-making process' attributes:Decision aids compared to usual care interventions resulted in:a) lower decisional conflict related to feeling uninformed (MD -7.26 of 100; 95% CI -9.73 to -4.78; n = 22) and feeling unclear about personal values (MD -6.09; 95% CI -8.50 to -3.67; n = 18);b) reduced proportions of people who were passive in decision making (RR 0.66; 95% CI 0.53 to 0.81; n = 14); andc) reduced proportions of people who remained undecided post-intervention (RR 0.59; 95% CI 0.47 to 0.72; n = 18).Decision aids appeared to have a positive effect on patient-practitioner communication in all nine studies that measured this outcome. For satisfaction with the decision (n = 20), decision-making process (n = 17), and/or preparation for decision making (n = 3), those exposed to a decision aid were either more satisfied, or there was no difference between the decision aid versus comparison interventions. No studies evaluated decision-making process attributes for helping patients to recognize that a decision needs to be made, or understanding that values affect the choice.C) Secondary outcomes Exposure to decision aids compared to usual care reduced the number of people of choosing major elective invasive surgery in favour of more conservative options (RR 0.79; 95% CI 0.68 to 0.93; n = 15). Exposure to decision aids compared to usual care reduced the number of people choosing to have prostate-specific antigen screening (RR 0.87; 95% CI 0.77 to 0.98; n = 9). When detailed compared to simple decision aids were used, fewer people chose menopausal hormone therapy (RR 0.73; 95% CI 0.55 to 0.98; n = 3). For other decisions, the effect on choices was variable.The effect of decision aids on length of consultation varied from 8 minutes shorter to 23 minutes longer (median 2.55 minutes longer) with 2 studies indicating statistically-significantly longer, 1 study shorter, and 6 studies reporting no difference in consultation length. Groups of patients receiving decision aids do not appear to differ from comparison groups in terms of anxiety (n = 30), general health outcomes (n = 11), and condition-specific health outcomes (n = 11). The effects of decision aids on other outcomes (adherence to the decision, costs/resource use) were inconclusive. AUTHORS' CONCLUSIONS: There is high-quality evidence that decision aids compared to usual care improve people's knowledge regarding options, and reduce their decisional conflict related to feeling uninformed and unclear about their personal values. There is moderate-quality evidence that decision aids compared to usual care stimulate people to take a more active role in decision making, and improve accurate risk perceptions when probabilities are included in decision aids, compared to not being included. There is low-quality evidence that decision aids improve congruence between the chosen option and the patient's values.New for this updated review is further evidence indicating more informed, values-based choices, and improved patient-practitioner communication. There is a variable effect of decision aids on length of consultation. Consistent with findings from the previous review, decision aids have a variable effect on choices. They reduce the number of people choosing discretionary surgery and have no apparent adverse effects on health outcomes or satisfaction. The effects on adherence with the chosen option, cost-effectiveness, use with lower literacy populations, and level of detail needed in decision aids need further evaluation. Little is known about the degree of detail that decision aids need in order to have a positive effect on attributes of the choice made, or the decision-making process.

An interactive, online decision aid assessing patient goals and preferences for treatment of aortic stenosis to support physician-led shared decision-making: Early feasibility pilot study.

BACKGROUND: Guidelines recommend shared decision making when choosing treatment for severe aortic stenosis but implementation has lagged. We assessed the feasibility and impact of a novel decision aid for severe aortic stenosis at point-of-care. METHODS: This prospective multi-site pilot cohort study included adults with severe aortic stenosis and their clinicians. Patients were referred by their heart team when scheduled to discuss treatment options. Outcomes included shared decision-making processes, communication quality, decision-making confidence, decisional conflict, knowledge, stage of decision making, decision quality, and perceptions of the tool. Patients were assessed at baseline (T0), after using the intervention (T1), and after the clinical encounter (T2); clinicians were assessed at T2. Before the encounter, patients reviewed the intervention, Aortic Valve Improved Treatment Approaches (AVITA), an interactive, online decision aid. AVITA presents options, frames decisions, clarifies patient goals and values, and generates a summary to use with clinicians during the encounter. RESULTS: 30 patients (9 women [30.0%]; mean [SD] age 70.4 years [11.0]) and 14 clinicians (4 women [28.6%], 7 cardiothoracic surgeons [50%]) comprised 28 clinical encounters Most patients [85.7%] and clinicians [84.6%] endorsed AVITA. Patients reported AVITA easy to use [89.3%] and helped them choose treatment [95.5%]. Clinicians reported the AVITA summary helped them understand their patients' values [80.8%] and make values-aligned recommendations [61.5%]. Patient knowledge significantly improved at T1 and T2 (p = 0.004). Decisional conflict, decision-making stage, and decision quality improved at T2 (p = 0.0001, 0.0005, and 0.083, respectively). Most patients [60%] changed treatment preference between T0 and T2. Initial treatment preferences were associated with low knowledge, high decisional conflict, and poor decision quality; final preferences were associated with high knowledge, low conflict, and high quality. CONCLUSIONS: AVITA was endorsed by patients and clinicians, easy to use, improved shared decision-making quality and helped patients and clinicians arrive at a treatment that reflected patients' values. TRIAL REGISTRATION: Trial ID: NCT04755426, Clinicaltrials.gov/ct2/show/NCT04755426.

Implementing Shared Decision-Making for Multiple Sclerosis: The MS-SUPPORT Tool.

BACKGROUND: Disease modifying therapies (DMTs) offer opportunities to improve the course of multiple sclerosis (MS), but decisions about treatment are difficult. People with multiple sclerosis (pwMS) want more involvement in decisions about DMTs, but new approaches are needed to support shared decision-making (SDM) because of the number of treatment options and the range of outcomes affected by treatment. We designed a patient-centered tool, MS-SUPPORT, to facilitate SDM for pwMS. We sought to evaluate the feasibility and impact of MS-SUPPORT on decisions about disease modifying treatments (DMTs), SDM processes, and quality-of-life. METHODS: This multisite randomized controlled trial compared the SDM intervention (MS-SUPPORT) to control (usual care) over a 12-month period. English-speaking adults with relapsing MS were eligible if they had an upcoming MS appointment and an email address. To evaluate clinician perspectives, participants' MS clinicians were invited to participate. Patients were referred between November 11, 2019 and October 23, 2020 by their MS clinician or a patient advocacy organization (the Multiple Sclerosis Association of America). MS-SUPPORT is an online, interactive, evidence-based decision aid that was co-created with pwMS. It clarifies patient treatment goals and values and provides tailored information about MS, DMTs, and adherence. Viewed by patients before their clinic appointment, MS-SUPPORT generates a personalized summary of the patient's treatment goals and preferences, adherence, DMT use, and clinical situation to share with their MS clinician. Outcomes (DMT utilization, adherence, quality-of-life, and SDM) were assessed at enrollment, post-MS-SUPPORT, post-appointment, and quarterly for 1 year. RESULTS: Participants included 501 adults with MS from across the USA (84.6% female, 83% white) and 34 of their MS clinicians (47% neurologists, 41% Nurse Practitioners, 12% Physician Assistants). Among the 203 patients who completed MS-SUPPORT, most (88.2%) reported they would recommend it to others and that it helped them talk to their doctor (85.2%), understand their options (82.3%) and the importance of taking DMTs as prescribed (82.3%). Among non-users of DMTs at baseline, the probability ratio of current DMT use consistently trended higher over one-year follow-up in the MS-SUPPORT group (1.30 [0.86-1.96]), as did the cumulative probability of starting a DMT within 6-months, with shorter time-to-start (46 vs 90 days, p=0.24). Among the 222 responses from 34 participating clinicians, more clinicians in the MS-SUPPORT group (vs control) trended towards recommending their patient start a DMT (9 of 108 (8%) vs 5 of 109 (5%), respectively, p=0.26). Adherence (no missed doses) to daily-dosed DMTs was higher in the MS-SUPPORT group (81.25% vs 56.41%, p=.026). Fewer patients forgot their doses (p=.046). The MS-SUPPORT group (vs control) reported 1.7 fewer days/month of poor mental health (p=0.02). CONCLUSIONS: MS-SUPPORT was strongly endorsed by patients and is feasible to use in clinical settings. MS-SUPPORT increased the short-term probability of taking and adhering to a DMT, and improved long-term mental health. Study limitations include selection bias, response bias, social desirability bias, and recall bias. Exploring approaches to reinforcement and monitoring its implementation in real-world settings should provide further insights into the value and utility of this new SDM tool.

Metformin and breast cancer risk: a meta-analysis and critical literature review.

Observational studies have suggested that metformin decreases the incidence of several common cancers. However, findings regarding breast cancer have been mixed. In order to explore this issue, a systematic literature review and meta-analysis were performed with a focus on potential biases. We conducted a comprehensive literature search for all pertinent studies addressing metformin use and breast cancer risk by searching PubMed, Cochrane Library, and Scopus (which includes Embase, ISI Web of Science) using the Mesh terms: "metformin" or "biguanides" or "diabetes mellitus, type 2/therapy" and "cancer" or "neoplasms." When multiple hazard ratios (HR) or odds ratio (OR) were reported, the most adjusted estimate was used in the base-case analysis. We pooled the adjusted HR and performed sensitivity analyses on duration of metformin use (> or ≤3 years use), study quality (assessed using the GRADE system), and initial observation year of the cohort (before vs after 1997). From a total of 443 citations, 18 full-text articles were considered, and seven independent studies were included. All were observational (four cohort and three case control). Our combined OR of all seven studies was 0.83 (0.71-0.97). Stronger associations were found when analyses were limited to studies estimating the impact of longer metformin use (OR = 0.75. 95 % CI 0.62, 0.91) or among studies that began observing their cohort before 1997 (OR = 0.68. 95 % CI 0.55-0.084). Stratification according to study quality did not affect the combined OR but higher quality studies had smaller CI and achieved statistical significance. Interpretation is limited by the observational nature of reports and different comparison groups. Our analyses support a protective effect of metformin on breast cancer risk among postmenopausal women with diabetes. Clinical trials are needed for definitive determination of the role of metformin in breast cancer risk reduction.

Factors associated with treatment of women with osteoporosis or osteopenia from a national survey.

BACKGROUND: Health outcomes could be improved if women at high risk for osteoporotic fracture were matched to effective treatment. This study determined the extent to which treatment for osteoporosis/osteopenia corresponded to the presence of specific risk factors for osteoporotic fracture. METHODS: This retrospective analysis of the United States 2007 National Health and Wellness Survey included women age ≥ 40 years who reported having a diagnosis of osteoporosis (69% of 3276) or osteopenia (31% of 3276). Patients were stratified by whether they were or were not taking prescription treatment for osteoporosis/osteopenia. Using 34 patient characteristics as covariates, logistic regression was used to determine factors associated with treatment. RESULTS: Current prescription treatment was reported by 1800 of 3276 (54.9%) women with osteoporosis/osteopenia. The following factors were associated with receiving prescription treatment: patient-reported diagnosis of osteoporosis (versus osteopenia); previous bone mineral density test; ≥ 2 fractures since age 50; older age; lower body mass index; better physical functioning; postmenopausal status; family history of osteoporosis; fewer comorbidities; prescription insurance coverage; higher total prescription count; higher ratio of prescription costs to monthly income; higher income; single status; previous visit to a rheumatologist or gynecologist; and 1 or 2 outpatient visits to healthcare provider (vs. none) in the prior 6 months. Glucocorticoid, tobacco, and daily alcohol use were risk factors for fracture that were not associated with treatment. CONCLUSIONS: There is a mismatch between those women who could benefit from treatment for osteoporosis and those who are actually treated. For example, self-reported use of glucocorticoids, tobacco, and alcohol were not associated with prescription treatment of osteoporosis. Other clinical and socioeconomic factors were associated with treatment (e.g. prescription drug coverage and higher income) or not (e.g. comorbid osteoarthritis and anxiety) and could be opportunities to improve care.

What matters most to patients with severe aortic stenosis when choosing treatment? Framing the conversation for shared decision making.

BACKGROUND: Guidelines recommend including the patient's values and preferences when choosing treatment for severe aortic stenosis (sAS). However, little is known about what matters most to patients as they develop treatment preferences. Our objective was to identify, prioritize, and organize patient-reported goals and features of treatment for sAS. METHODS: This multi-center mixed-methods study conducted structured focus groups using the nominal group technique to identify patients' most important treatment goals and features. Patients separately rated and grouped those items using card sorting techniques. Multidimensional scaling and hierarchical cluster analyses generated a cognitive map and clusters. RESULTS: 51 adults with sAS and 3 caregivers with experience choosing treatment (age 36-92 years) were included. Participants were referred from multiple health centers across the U.S. and online. Eight nominal group meetings generated 32 unique treatment goals and 46 treatment features, which were grouped into 10 clusters of goals and 11 clusters of features. The most important clusters were: 1) trust in the healthcare team, 2) having good information about options, and 3) long-term outlook. Other clusters addressed the need for and urgency of treatment, being independent and active, overall health, quality of life, family and friends, recovery, homecare, and the process of decision-making. CONCLUSIONS: These patient-reported items addressed the impact of the treatment decision on the lives of patients and their families from the time of decision-making through recovery, homecare, and beyond. Many attributes had not been previously reported for sAS. The goals and features that patients' value, and the relative importance that they attach to them, differ from those reported in clinical trials and vary substantially from one individual to another. These findings are being used to design a shared decision-making tool to help patients and their clinicians choose a treatment that aligns with the patients' priorities. TRIAL REGISTRATION: ClinicalTrials.gov, Trial ID: NCT04755426, Trial URL https://clinicaltrials.gov/ct2/show/NCT04755426.

Decision aids for people facing health treatment or screening decisions.

BACKGROUND: Decision aids prepare people to participate in decisions that involve weighing benefits, harms, and scientific uncertainty. OBJECTIVES: To evaluate the effectiveness of decision aids for people facing treatment or screening decisions. SEARCH STRATEGY: For this update, we searched from January 2006 to December 2009 in MEDLINE (Ovid); Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library, issue 4 2009); CINAHL (Ovid) (to September 2008 only); EMBASE (Ovid); PsycINFO (Ovid); and grey literature. Cumulatively, we have searched each database since its start date. SELECTION CRITERIA: We included published randomised controlled trials (RCTs) of decision aids, which are interventions designed to support patients' decision making by providing information about treatment or screening options and their associated outcomes, compared to usual care and/or alternative interventions. We excluded studies in which participants were not making an active treatment or screening decision. DATA COLLECTION AND ANALYSIS: Two review authors independently screened abstracts for inclusion, extracted data, and assessed potential risk of bias. The primary outcomes, based on the International Patient Decision Aid Standards, were:A) decision attributes;B) decision making process attributes.Secondary outcomes were behavioral, health, and health system effects. We pooled results of RCTs using mean differences (MD) and relative risks (RR), applying a random effects model. MAIN RESULTS: Of 34,316 unique citations, 86 studies involving 20,209 participants met the eligibility criteria and were included. Thirty-one of these studies are new in this update. Twenty-nine trials are ongoing. There was variability in potential risk of bias across studies. The two criteria that were most problematic were lack of blinding and the potential for selective outcome reporting, given that most of the earlier trials were not registered.Of 86 included studies, 63 (73%) used at least one measure that mapped onto an IPDAS effectiveness criterion: A) criteria involving decision attributes: knowledge scores (51 studies); accurate risk perceptions (16 studies); and informed value-based choice (12 studies); and B) criteria involving decision process attributes: feeling informed (30 studies) and feeling clear about values (18 studies).A) Criteria involving decision attributes:Decision aids performed better than usual care interventions by increasing knowledge (MD 13.77 out of 100; 95% confidence interval (CI) 11.40 to 16.15; n = 26). When more detailed decision aids were compared to simpler decision aids, the relative improvement in knowledge was significant (MD 4.97 out of 100; 95% CI 3.22 to 6.72; n = 15). Exposure to a decision aid with expressed probabilities resulted in a higher proportion of people with accurate risk perceptions (RR 1.74; 95% CI 1.46 to 2.08; n = 14). The effect was stronger when probabilities were expressed in numbers (RR 1.93; 95% CI 1.58 to 2.37; n = 11) rather than words (RR 1.27; 95% CI 1.09 to 1.48; n = 3). Exposure to a decision aid with explicit values clarification compared to those without explicit values clarification resulted in a higher proportion of patients achieving decisions that were informed and consistent with their values (RR 1.25; 95% CI 1.03 to 1.52; n = 8).B) Criteria involving decision process attributes:Decision aids compared to usual care interventions resulted in: a) lower decisional conflict related to feeling uninformed (MD -6.43 of 100; 95% CI -9.16 to -3.70; n = 17); b) lower decisional conflict related to feeling unclear about personal values (MD -4.81; 95% CI -7.23 to -2.40; n = 14); c) reduced the proportions of people who were passive in decision making (RR 0.61; 95% CI 0.49 to 0.77; n = 11); and d) reduced proportions of people who remained undecided post-intervention (RR 0.57; 95% CI 0.44 to 0.74; n = 9). Decision aids appear to have a positive effect on patient-practitioner communication in the four studies that measured this outcome. For satisfaction with the decision (n = 12) and/or the decision making process (n = 12), those exposed to a decision aid were either more satisfied or there was no difference between the decision aid versus comparison interventions. There were no studies evaluating the decision process attributes relating to helping patients to recognize that a decision needs to be made or understand that values affect the choice.C) Secondary outcomesExposure to decision aids compared to usual care continued to demonstrate reduced choice of: major elective invasive surgery in favour of conservative options (RR 0.80; 95% CI 0.64 to 1.00; n = 11). Exposure to decision aids compared to usual care also resulted in reduced choice of PSA screening (RR 0.85; 95% CI 0.74 to 0.98; n = 7). When detailed compared to simple decision aids were used, there was reduced choice of menopausal hormones (RR 0.73; 95% CI 0.55 to 0.98; n = 3). For other decisions, the effect on choices was variable. The effect of decision aids on length of consultation varied from -8 minutes to +23 minutes (median 2.5 minutes). Decision aids do not appear to be different from comparisons in terms of anxiety (n = 20), and general health outcomes (n = 7), and condition specific health outcomes (n = 9). The effects of decision aids on other outcomes (adherence to the decision, costs/resource use) were inconclusive. AUTHORS' CONCLUSIONS: New for this updated review is evidence that: decision aids with explicit values clarification exercises improve informed values-based choices; decision aids appear to have a positive effect on patient-practitioner communication; and decision aids have a variable effect on length of consultation.Consistent with findings from the previous review, which had included studies up to 2006: decision aids increase people's involvement, and improve knowledge and realistic perception of outcomes; however, the size of the effect varies across studies. Decision aids have a variable effect on choices. They reduce the choice of discretionary surgery and have no apparent adverse effects on health outcomes or satisfaction. The effects on adherence with the chosen option, patient-practitioner communication, cost-effectiveness, and use with developing and/or lower literacy populations need further evaluation. Little is known about the degree of detail that decision aids need in order to have positive effects on attributes of the decision or decision-making process.

Decision aids for people facing health treatment or screening decisions.

BACKGROUND: Decision aids prepare people to participate in 'close call' decisions that involve weighing benefits, harms, and scientific uncertainty. OBJECTIVES: To conduct a systematic review of randomised controlled trials (RCTs) evaluating the efficacy of decision aids for people facing difficult treatment or screening decisions. SEARCH STRATEGY: We searched MEDLINE (Ovid) (1966 to July 2006); Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library; 2006, Issue 2); CINAHL (Ovid) (1982 to July 2006); EMBASE (Ovid) (1980 to July 2006); and PsycINFO (Ovid) (1806 to July 2006). We contacted researchers active in the field up to December 2006. There were no language restrictions. SELECTION CRITERIA: We included published RCTs of interventions designed to aid patients' decision making by providing information about treatment or screening options and their associated outcomes, compared to no intervention, usual care, and alternate interventions. We excluded studies in which participants were not making an active treatment or screening decision, or if the study's intervention was not available to determine that it met the minimum criteria to qualify as a patient decision aid. DATA COLLECTION AND ANALYSIS: Two review authors independently screened abstracts for inclusion, and extracted data from included studies using standardized forms. The primary outcomes focused on the effectiveness criteria of the International Patient Decision Aid Standards (IPDAS) Collaboration: attributes of the decision and attributes of the decision process. We considered other behavioural, health, and health system effects as secondary outcomes. We pooled results of RCTs using mean differences (MD) and relative risks (RR) using a random effects model. MAIN RESULTS: This update added 25 new RCTs, bringing the total to 55. Thirty-eight (69%) used at least one measure that mapped onto an IPDAS effectiveness criterion: decision attributes: knowledge scores (27 trials); accurate risk perceptions (11 trials); and value congruence with chosen option (4 trials); and decision process attributes: feeling informed (15 trials) and feeling clear about values (13 trials).This review confirmed the following findings from the previous (2003) review. Decision aids performed better than usual care interventions in terms of: a) greater knowledge (MD 15.2 out of 100; 95% CI 11.7 to 18.7); b) lower decisional conflict related to feeling uninformed (MD -8.3 of 100; 95% CI -11.9 to -4.8); c) lower decisional conflict related to feeling unclear about personal values (MD -6.4; 95% CI -10.0 to -2.7); d) reduced the proportion of people who were passive in decision making (RR 0.6; 95% CI 0.5 to 0.8); and e) reduced proportion of people who remained undecided post-intervention (RR 0.5; 95% CI 0.3 to 0.8). When simpler decision aids were compared to more detailed decision aids, the relative improvement was significant in knowledge (MD 4.6 out of 100; 95% CI 3.0 to 6.2) and there was some evidence of greater agreement between values and choice.In this review, we were able to explore the use of probabilities in decision aids. Exposure to a decision aid with probabilities resulted in a higher proportion of people with accurate risk perceptions (RR 1.6; 95% CI 1.4 to 1.9). The effect was stronger when probabilities were measured quantitatively (RR 1.8; 95% CI 1.4 to 2.3) versus qualitatively (RR 1.3; 95% CI 1.1 to 1.5).As in the previous review, exposure to decision aids continued to demonstrate reduced rates of: elective invasive surgery in favour of conservative options, decision aid versus usual care (RR 0.8; 95% CI 0.6 to 0.9); and use of menopausal hormones, detailed versus simple aid (RR 0.7; 95% CI 0.6 to 1.0). There is now evidence that exposure to decision aids results in reduced PSA screening, decision aid versus usual care (RR 0.8; 95% CI 0.7 to 1.0) . For other decisions, the effect on decisions remains variable.As in the previous review, decision aids are no better than comparisons in affecting satisfaction with decision making, anxiety, and health outcomes. The effects of decision aids on other outcomes (patient-practitioner communication, consultation length, continuance, resource use) were inconclusive.There were no trials evaluating the IPDAS decision process criteria relating to helping patients to recognize a decision needs to be made, understand that values affect the decision, or discuss values with the practitioner. AUTHORS' CONCLUSIONS: Patient decision aids increase people's involvement and are more likely to lead to informed values-based decisions; however, the size of the effect varies across studies. Decision aids have a variable effect on decisions. They reduce the use of discretionary surgery without apparent adverse effects on health outcomes or satisfaction. The degree of detail patient decision aids require for positive effects on decision quality should be explored. The effects on continuance with chosen option, patient-practitioner communication, consultation length, and cost-effectiveness need further evaluation.

Revisiting the duration of vasomotor symptoms of menopause: a meta-analysis.

BACKGROUND: Treatment decisions about menopause are predicated on a transient duration of vasomotor symptoms. However, evidence supporting a specific duration is weak. OBJECTIVE: To estimate the natural progression of vasomotor symptoms during the menopause transition by systematically compiling available evidence using meta-analytic techniques. DATA SOURCES: We searched MEDLINE, hand searched secondary references in relevant studies, book chapters, and review papers, and contacted investigators about relevant published research. REVIEW METHODS: English language, population-based studies reporting vasomotor symptom prevalence among women in menopausal transition in time intervals based on years to or from final menstrual period were included. Two reviewers independently assessed eligibility and quality of studies and extracted data for vasomotor symptom prevalence. RESULTS: The analyses included 10 studies (2 longitudinal, 8 cross sectional) with 35,445 participants. The percentage of women experiencing symptoms increased sharply in the 2 years before final menstrual period, peaked 1 year after final menstrual period, and did not return to premenopausal levels until about 8 years after final menstrual period. Nearly 50% of all women reported vasomotor symptoms 4 years after final menstrual period, and 10% of all women reported symptoms as far as 12 years after final menstrual period. When data were examined according to symptom severity ('any' vs. 'bothersome'), bothersome symptoms peaked about 1 year earlier and declined more rapidly than symptoms of any severity level. CONCLUSIONS: Our findings suggest a median symptom duration of about 4 years among symptomatic women. A longer symptom duration may affect treatment decisions and clinical guidelines. Further prospective, longitudinal studies of menopausal symptoms should be conducted to confirm these results.

Whose Preferences Matter? A Patient-Centered Approach for Eliciting Treatment Goals.

BACKGROUND: Patients facing a high-stakes clinical decision are often confronted with an overwhelming array of options. High-quality decisions about treatment should reflect patients' preferences as well as their clinical characteristics. Preference-assessment instruments typically focus on pre-selected clinical outcomes and attributes chosen by the investigator. OBJECTIVE: We sought to develop a patient-centered approach to elicit and compare the treatment goals of patients with multiple sclerosis (MS) and healthcare providers (HCPs). METHODS: We conducted five nominal group technique (NGT) meetings to elicit and prioritize treatment goals from patients and HCPs. Five to nine participants in each group responded silently to one question about their treatment goals. Responses were shared, consolidated, and ranked to develop a prioritized list for each group. The ranked lists were combined. Goals were rated and sorted into categories. Multidimensional scaling and hierarchical cluster analysis were used to derive a visual representation, or cognitive map, of the data and to identify conceptual clusters, reflecting how frequently items were sorted into the same category. RESULTS: Five NGT groups yielded 34 unique patient-generated treatment goals and 31 unique HCP-generated goals. There were differences between patients and HCPs in the goals generated and how they were clustered. Patients' goals tended to focus on the impact of specific symptoms on their day-to-day lives, whereas providers' goals focused on slowing down the course of disease progression. CONCLUSIONS: Differences between the treatment goals of patients and HCPs underscore the limitations of using HCP- or investigator-identified goals. This new adaptation of cognitive mapping is a patient-centered approach that can be used to generate and organize the outcomes and attributes for values clarification exercises while minimizing investigator bias and maximizing relevance to patients.

Evaluation of a Novel Preference Assessment Tool for Patients with Multiple Sclerosis.

BACKGROUND: We developed a preference assessment tool to help assess patient goals, values, and preferences for multiple sclerosis (MS) management. All preference items in the tool were generated by people with MS. The aim of this study was to evaluate this tool in a national sample of people with MS. METHODS: English-speaking patients with MS aged 21 to 75 years with access to the internet were recruited. Participants completed the preference tool online, which included separate modules assessing three core preference areas: treatment goals, preferences for attributes of disease-modifying therapies, and factors influencing a change in treatment. The tool generated a summary of participants' treatment goals and preferences. Immediately after viewing the summary, participants were asked to evaluate the tool. Rankings of preference domains were compared with rankings obtained in another study. RESULTS: In 135 people with MS who completed the tool and evaluation, the highest ranked goal was brain health (memory, thinking, brain), followed by disability concerns (walking, strength, vision). Rankings were highly similar to those in the referent study. Nearly all participants reported that the tool helped them understand their goals and priorities regarding MS and that the summary appropriately reflected what is important to them. Most participants (87%) wanted to discuss their treatment goals and priorities with their clinician. CONCLUSIONS: This preference assessment tool successfully captured patients' goals, values, and preferences for MS treatment and could potentially be used to help patients communicate their preferences to their clinician.

Hormone therapy for the prevention of bone loss in menopausal women with osteopenia: is it a viable option?

Osteopenia is a state of low bone mass, the appropriate clinical management of which is not always clear. The use of hormone therapy for postmenopausal bone loss has become controversial given recent data regarding the risks of therapy. Fragility fractures are common, and result in substantial morbidity and mortality. Although the fracture rate is higher among osteoporotic women, the substantially larger population of osteopenic women accounts for a higher absolute number of fractures. Osteopenia is defined solely according to the statistical properties of the distribution of bone mineral density (BMD) values, which limits its usefulness in clinical care. BMD, although inversely related to fracture risk, should not be used as the sole criterion for fracture risk. Limited data suggest that benefits of treatment seen in women with documented osteoporosis may not extend to osteopenic women. Although estrogen prevents postmenopausal bone loss, preservation of BMD does not necessarily translate into reduced fracture risk. In making decisions about whether to treat a woman with osteopenia, it is critical to estimate how treatments will affect the individual's risk of fracture. Treatment decisions should be based on whether the net benefits of treatment outweigh the anticipated risks, which will depend on the age of the patient and her risk profile. In our opinion, there is insufficient evidence to support treatment for women with a BMD in the osteopenic range in the absence of fragility fracture. For osteopenic women with higher risk, the availability of other treatments with a more favourable risk-benefit profile eliminates the role of hormone therapy for fracture prevention.

Using Internet technologies to improve and simplify counseling about menopause: the WISDOM website.

Although much attention has been given to measuring the risks associated with menopausal hormone therapy (HT), decisions about HT should be guided largely by individual patient preferences and values. Because the magnitude of the risks associated with HT for healthy 50-year-old women are exceedingly small (typically <1 in 1000) and its impact on survival are negligible, patient preferences and values become the most critical considerations. To make a rational and informed decision about HT, a woman needs to weigh any short-term gains in quality of life from HT against its longer term risks. To do this, clinicians need to gauge the patient's risks for the conditions affected by HT, the effects of HT on these risks, understand the woman's menopausal symptoms and identify the best treatment. This can be time consuming and challenging for clinicians to perform, and appears to be rarely done in clinical practice. Decision support tools can more rationally use available resources by shifting responsibilities away from those least able to perform them towards those most appropriate to perform them. The Internet presents new opportunities for delivering and disseminating individualized decision support tools that can help with menopausal counseling. A web-based decision support tool, Women's Interactive System about Decision On Menopause (WISDOM), was designed to improve the quality of treatment decisions around menopause and HT by providing individualized information about the impact of menopausal treatments on symptoms and risks. Preliminary trial results suggest a positive impact on clinicians and patients. The unique challenges and opportunities in developing and testing web-based decision support tools are discussed.

Communicating the uncertainty of harms and benefits of medical interventions.

BACKGROUND: There is growing interest in shared medical decision making among patients, physicians, and policy makers. This requires patients to interpret increasing amounts of medical information, much of which is uncertain. Little is known about the optimal approaches to or outcomes of communicating uncertainty about the risks and benefits of treatments. METHODS: The authors reviewed the literature on various issues related to uncertainty in decision making: conceptualizing uncertainty, identifying its potential sources, assessing uncertainty, potential methods of communicating uncertainty, potential outcomes of communicating uncertainty, and current practices and recommendations by expert groups on communicating uncertainty. RESULTS: There are multiple sources of uncertainty in most medical decisions. There are conceptual differences in how researchers define uncertainty and its sources, as well as in its measurement. The few studies that have assessed alternate means of communicating uncertainty dealt mostly with presenting uncertainty about probabilities. Both patients' and physicians' interpretation of and responses to uncertainty may depend on their personal characteristics and values and may be affected by the manner in which uncertainty is communicated. CONCLUSIONS: Research has not yet identified best practices for communicating uncertainty to patients about harms and benefits of treatment. More conceptual, qualitative, and quantitative studies are needed to explore fundamental questions about how people process, interpret, and respond to various types of uncertainty inherent in clinical decisions.

Can computerized decision support help patients make complex treatment decisions? A randomized controlled trial of an individualized menopause decision aid.

PURPOSE: To compare the effectiveness of an individualized decision aid (DA) with standard educational materials on decisions about menopausal treatments and to assess the feasibility of integrating this DA into clinical practice, with and without coaching. METHODS: We conducted a 3-armed randomized controlled trial in 3 clinics, enrolling menopausal women between the ages of 45 and 65 years with primary care appointments. Of the 145 women included, 99 completed a 2-week follow-up. The control group received generic educational materials, 1 intervention group received an individualized computer-generated DA mailed to patients and their clinicians before clinic appointment, and the 2nd intervention group received the same DA along with coached care before clinic appointment (DA + CC). Decisional conflict, satisfaction, and knowledge were measured 2 weeks after clinic appointment. RESULTS: Participants' mean age was 52 years, and 97% were white. Most women (98%) read all or most of the documents. Decisional conflict was significantly lower in both intervention groups but not in the control group. DA reduced decisional conflict from preintervention to postintervention (pre-post change) by 0.70 (SD = 0.56) points (on a 1-5 scale), compared to reductions of 0.51 (SD = 0.51) and 0.09 (SD = 0.44) for the DA + CC group and the control group, respectively. Satisfaction with the decision made was significantly higher at 2 weeks in the DA v. control group. Self-reported knowledge significantly improved in DA + CC compared to controls. CONCLUSION: Our decision aid lowered decisional conflict and improved patient satisfaction; adding coaching provided little additional benefit.

Do patient decision aids meet effectiveness criteria of the international patient decision aid standards collaboration? A systematic review and meta-analysis.

OBJECTIVE: To describe the extent to which patient decision aids (PtDAs) meet effectiveness standards of the International Patient Decision Aids Collaboration (IPDAS). DATA SOURCES: Five electronic databases (to July 2006) and personal contacts (to December 2006). RESULTS: Among 55 randomized controlled trials, 38 (69%) used at least 1 measure that mapped onto an IPDAS effectiveness criterion. Measures of decision quality were knowledge scores (27 trials), accurate risk perceptions (12 trials), and value congruence with the chosen option (3 trials). PtDAs improved knowledge scores relative to usual care (weighted mean difference [WMD] = 15.2%, 95% confidence interval [CI] = 11.7 to 18.7); detailed PtDAs were somewhat more effective than simpler PtDAs (WMD = 4.6%, 95% CI = 3.0 to 6.2). PtDAs with probabilities improved accurate risk perceptions relative to those without probabilities (relative risk = 1.6, 95% CI = 1.4 to 1.9). Relative to simpler PtDAs, detailed PtDAs improved value congruence with the chosen option. Only 2 of 6 IPDAS decision process criteria were measured: feeling informed (15 trials) and feeling clear about values (13 trials). PtDAs improved these process measures relative to usual care (feeling uninformed WMD = -8.4, 95% CI = -11.9 to -4.8; unclear values WMD = -6.3, 95% CI = -10.0 to -2.7). There was no difference in process measures when detailed and simple PtDAs were compared. CONCLUSIONS: PtDAs improve decision quality and the decision process's measures of feeling informed and clear about values; however, the size of the effect varies across studies. Several IPDAS decision process measures have not been used. Future trials need to use a minimum data set of IPDAS evaluation measures. The degree of detail PtDAs require for positive effects on IPDAS criteria should be explored.

Impact and Feasibility of Personalized Decision Support for Older Patients with Diabetes: A Pilot Randomized Trial.

BACKGROUND: Diabetes guidelines recommend individualizing glycemic goals (A1C) for older patients. The aim of this study was to assess a personalized Web-based decision support tool. METHODS: We randomized physicians and their patients with type 2 diabetes (≥65 years of age) to a support tool or educational pamphlet (75:25 patients). Prior to a visit, intervention patients interacted with the tool, which provided personalized risk predictions and elicited treatment preferences. Main outcomes included 1) patient-doctor communication, 2) decisional conflict, 3) changes in goals, and 4) intervention acceptability. RESULTS: We did not find significant differences in proportions of patients who had an A1C discussion (91% intervention v. 76% control; P = 0.19). Intervention patients had larger declines in the informed subscale of decisional conflict (-20 v. 0, respectively; P = 0.04). There were no significant differences in proportions of patients with changes in goals (49% v. 28%, respectively; P = 0.08). Most intervention patients reported that the tool was easy to use (91%) and helped them to communicate (84%). A limitation was that this was a pilot trial at one academic institution. CONCLUSIONS: Web-based decision support tools may be a practical approach to facilitating the personalization of goals for chronic conditions. TRIAL REGISTRATION: NCT02169999 ( https://clinicaltrials.gov/show/NCT02169999 ).