背景:不同的指南面板,和个人,可能会部分根据他们的偏好做出不同的决定。支持或反对干预的偏好被视为人们对预期或经历的健康结果的相对重视的结果。然后,当平衡对筛查计划临床有效性的经验证据所报告的益处和危害的影响估计时,这些发现可被视为患者输入。这项系统评价更新研究了患者对基于乳房X线摄影的乳腺癌筛查的潜在益处和危害的相对重要性,以更新2018年加拿大预防保健工作组的筛查指南。
方法:我们从以前的评论中筛选了所有文章(搜索2017年12月),并在MEDLINE中将搜索更新至2023年6月19日,PsycINFO,和CINAHL。我们还筛选了灰色文献,利益相关者提交的文件,和参考列表。目标人群是顺性女性和其他出生时分配女性的成年人(包括跨性别男性和非二元人群),年龄≥35岁,平均或中度增加患乳腺癌的风险。对乳腺癌患者的研究符合相关结果的健康状况效用数据。我们寻找三种类型的数据,直接通过(i)筛查和治疗健康状况(测量结果对健康相关生活质量的影响;以0[死亡]至1[完美健康]的量表测量的效用),和(Ii)其他基于偏好的数据,比如结果权衡,并间接地通过(Iii)从态度推断的利益与伤害的相对重要性,意图,和筛选患者的行为提供了对益处和危害大小的估计。对于筛选,在至少50%的研究已经由人类重复审查后,我们使用机器学习作为审查者之一;全文选择使用由两个人进行的独立审查.数据提取和偏差风险评估使用单个审阅者进行验证。我们对公用事业的主要分析使用了来自基于公用事业的健康相关生活质量工具的数据(例如,EQ-5D)在患者中;对于加拿大公众来说,约0.04的无效值可以被认为是最低的重要值。如果合适,我们汇集了公用事业,探索了异质性。计算了用于筛选健康状态和不同治疗状态之间的功能缺陷。非公用事业数据分为几类,根据比较的结果(例如权衡数据),参与者年龄,以及我们对研究描绘的筛查净收益的判断。此后,我们在考虑样本量的同时比较和对比研究结果,偏见的风险,关于知识得分的分组结果和数据,并为每个数据集创建摘要语句。确定性评估遵循GRADE对患者偏好的指导,并在至少两名审阅者之间达成共识。
结果:纳入了82项研究(38项关于公用事业)。阳性筛查结果(中度确定性)的估计废液为0.07,0.03-0.04的假阳性(FP;“额外测试”解析为癌症阴性)(低确定性),对于未经处理的筛查检测到的癌症(中度确定性)或(低确定性)间隔癌症,则为0.08。≤12个月时,乳房切除术的功能性(vs.保乳治疗),化疗(vs.无)(低确定性),和放射治疗(vs.无)(中等确定性)为0.02-0.03、0.02-0.04,几乎无,分别,尽管在每种情况下,研究结果的适用性都有些有限。从长远来看,乳房切除术与保乳手术/乳房肿瘤切除术联合放疗和放疗的不成功者之间存在中度确定性。有适度的确定性,大多数(>50%)和可能的绝大多数(>75%)的女性可能接受多达6例的过度诊断,以防止一例乳腺癌死亡;有一些不确定性,因为在某些情况下,参与者没有完全理解过度诊断。低确定性的证据表明,绝大多数人可能接受筛查可以降低乳腺癌,但不是全因死亡率。至少在乳腺癌死亡率降低率相对较高的情况下(n=2;每1000个筛查减少2和5个),并且至少大多数人接受,为了防止一例乳腺癌死亡,至少有几百名患者将获得FP结果,10-15名患者将通过活检解决FP。未评估可接受的FP数量的上限。当使用评估态度的研究数据时,意图,和筛选行为,在所有年龄组中,但最明显的是40多岁的女性,偏好随着研究作者提出的净收益的减少而减少。在净收益相对较低的情况下,大多数40岁以下的患者可能没有权衡筛查带来的益处大于危害,而50岁以下的女性则可能更喜欢筛查(这两个年龄段的患者的确定性较低).可以肯定的是,大多数50岁和50至69岁的女性,他们通常经历过筛查,在高净收益的情况下,权衡筛查带来的收益大于危害。最近进行过筛查的70-71岁的绝大多数患者可能认为继续进行筛查的好处大于危害。大多数70年代中期至80年代初的女性可能更喜欢继续筛查。
结论:关于知情患者如何重视乳腺癌筛查的潜在结果的一系列数据来源的证据将在决策中提供建议。证据表明,所有检查的结果对任何年龄的女性都很重要,至少有一些可能是实质性的(在40多岁的人群中)在年龄组之间和年龄组内关于结果之间可接受的影响程度的差异,并且可能需要提供有关结果可能性的易于理解的信息,以便能够做出明智的决策。虽然研究来自广泛的国家,来自加拿大的数据有限,关于研究结果是否适用于人种学和社会经济多样化的人群.
背景:开放科学框架https://osf.io/xngsu/提供的协议。
BACKGROUND: Different guideline panels, and individuals, may make different decisions based in part on their preferences. Preferences for or against an intervention are viewed as a consequence of the relative importance people place on the expected or experienced health outcomes it incurs. These findings can then be considered as patient input when balancing effect estimates on benefits and harms reported by empirical evidence on the clinical effectiveness of screening programs. This systematic
review update examined the relative importance placed by patients on the potential benefits and harms of mammography-based breast cancer screening to inform an update to the 2018 Canadian Task Force on Preventive Health Care\'s guideline on screening.
METHODS: We screened all articles from our previous
review (search December 2017) and updated our searches to June 19, 2023 in MEDLINE, PsycINFO, and CINAHL. We also screened grey literature, submissions by stakeholders, and reference lists. The target population was cisgender women and other adults assigned female at birth (including transgender men and nonbinary persons) aged ≥ 35 years and at average or moderately increased risk for breast cancer. Studies of patients with breast cancer were eligible for health-state utility data for relevant outcomes. We sought three types of data, directly through (i) disutilities of screening and curative treatment health states (measuring the impact of the outcome on one\'s health-related quality of life; utilities measured on a scale of 0 [death] to 1 [perfect health]), and (ii) other preference-based data, such as outcome trade-offs, and indirectly through (iii) the relative importance of benefits versus harms inferred from attitudes, intentions, and behaviors towards screening among patients provided with estimates of the magnitudes of benefit(s) and harms(s). For screening, we used machine learning as one of the reviewers after at least 50% of studies had been reviewed in duplicate by humans; full-text selection used independent
review by two humans. Data extraction and risk of bias assessments used a single reviewer with verification. Our main analysis for utilities used data from utility-based health-related quality of life tools (e.g., EQ-5D) in patients; a disutility value of about 0.04 can be considered a minimally important value for the Canadian public. When suitable, we pooled utilities and explored heterogeneity. Disutilities were calculated for screening health states and between different treatment states. Non-utility data were grouped into categories, based on outcomes compared (e.g. for trade-off data), participant age, and our judgements of the net benefit of screening portrayed by the studies. Thereafter, we compared and contrasted findings while considering sample sizes, risk of bias, subgroup findings and data on knowledge scores, and created summary statements for each data set. Certainty assessments followed GRADE guidance for patient preferences and used consensus among at least two reviewers.
RESULTS: Eighty-two studies (38 on utilities) were included. The estimated disutilities were 0.07 for a positive screening result (moderate certainty), 0.03-0.04 for a false positive (FP; \"additional testing\" resolved as negative for cancer) (low certainty), and 0.08 for untreated screen-detected cancer (moderate certainty) or (low certainty) an interval cancer. At ≤12 months, disutilities of mastectomy (vs. breast-conserving therapy), chemotherapy (vs. none) (low certainty), and radiation therapy (vs. none) (moderate certainty) were 0.02-0.03, 0.02-0.04, and little-to-none, respectively, though in each case findings were somewhat limited in their applicability. Over the longer term, there was moderate certainty for little-to-no disutility from mastectomy versus breast-conserving surgery/lumpectomy with radiation and from radiation. There was moderate certainty that a majority (>50%) and possibly a large majority (>75%) of women probably accept up to six cases of overdiagnosis to prevent one breast-cancer death; there was some uncertainty because of an indication that overdiagnosis was not fully understood by participants in some cases. Low certainty evidence suggested that a large majority may accept that screening may reduce breast-cancer but not all-cause mortality, at least when presented with relatively high rates of breast-cancer mortality reductions (n = 2; 2 and 5 fewer per 1000 screened), and at least a majority accept that to prevent one breast-cancer death at least a few hundred patients will receive a FP result and 10-15 will have a FP resolved through biopsy. An upper limit for an acceptable number of FPs was not evaluated. When using data from studies assessing attitudes, intentions, and screening behaviors, across all age groups but most evident for women in their 40s, preferences reduced as the net benefit presented by study authors decreased in magnitude. In a relatively low net-benefit scenario, a majority of patients in their 40s may not weigh the benefits as greater than the harms from screening whereas for women in their 50s a large majority may prefer screening (low certainty evidence for both ages). There was moderate certainty that a large majority of women 50 years of age and 50 to 69 years of age, who have usually experienced screening, weigh the benefits as greater than the harms from screening in a high net-benefit scenario. A large majority of patients aged 70-71 years who have recently screened probably think the benefits outweigh the harms of continuing to screen. A majority of women in their mid-70s to early 80s may prefer to continue screening.
CONCLUSIONS: Evidence across a range of data sources on how informed patients value the potential outcomes from breast-cancer screening will be useful during decision-making for recommendations. The evidence suggests that all of the outcomes examined have importance to women of any age, that there is at least some and possibly substantial (among those in their 40s) variability across and within age groups about the acceptable magnitude of effects across outcomes, and that provision of easily understandable information on the likelihood of the outcomes may be necessary to enable informed decision making. Although studies came from a wide range of countries, there were limited data from Canada and about whether findings applied well across an ethnographically and socioeconomically diverse population.
BACKGROUND: Protocol available at Open Science Framework https://osf.io/xngsu/ .