Mühlbauer Viktoria, Berger-Höger Birte, Albrecht Martina, Mühlhauser Ingrid, Steckelberg Anke
MIN Faculty, Health Sciences and Education, University of Hamburg, Martin-Luther-King Platz 6, D-20146, Hamburg, Germany.
Institute for Health and Nursing Science, Martin Luther University Halle-Wittenberg, Magdeburger Str. 8, D-06112, Halle, Germany.
BMC Health Serv Res. 2019 Mar 15;19(1):171. doi: 10.1186/s12913-019-3988-2.
Shared decision-making in oncology requires information on individual prognosis. This comprises cancer prognosis as well as competing risks of dying due to age and comorbidities. Decision aids usually do not provide such information on competing risks. We conducted an overview on clinical prediction tools for early breast cancer and developed and pilot-tested a decision aid (DA) addressing individual prognosis using additional chemotherapy in early, hormone receptor-positive breast cancer as an example.
Systematic literature search on clinical prediction tools for the effects of drug treatment on survival of breast cancer. The DA was developed following criteria for evidence-based patient information and International Patient Decision Aids Standards. We included data on the influence of age and comorbidities on overall prognosis. The DA was pilot-tested in focus groups. Comprehension was additionally evaluated through an online survey with women in breast cancer self-help groups.
We identified three prediction tools: Adjuvant!Online, PREDICT and CancerMath. All tools consider age and tumor characteristics. Adjuvant!Online considers comorbidities, CancerMath displays age-dependent non-cancer mortality. Harm due to therapy is not reported. Twenty women participated in focus groups piloting the DA until data saturation was achieved. A total of 102 women consented to participate in the online survey, of which 86 completed the survey. The rate of correct responses was 90.5% and ranged between 84 and 95% for individual questions.
None of the clinical prediction tools fulfilled the requirements to provide women with all the necessary information for informed decision-making. Information on individual prognosis was well understood and can be included in patient decision aids.
肿瘤学中的共同决策需要个体预后信息。这包括癌症预后以及因年龄和合并症导致的竞争性死亡风险。决策辅助工具通常不提供关于竞争性风险的此类信息。我们对早期乳腺癌的临床预测工具进行了综述，并以早期激素受体阳性乳腺癌使用辅助化疗为例，开发并进行了一项针对个体预后的决策辅助工具（DA）的试点测试。
对药物治疗对乳腺癌生存影响的临床预测工具进行系统文献检索。该决策辅助工具是根据循证患者信息标准和国际患者决策辅助工具标准开发的。我们纳入了年龄和合并症对总体预后影响的数据。该决策辅助工具在焦点小组中进行了试点测试。此外，通过对乳腺癌自助小组中的女性进行在线调查来评估理解情况。
我们确定了三种预测工具：Adjuvant!Online、PREDICT和CancerMath。所有工具都考虑年龄和肿瘤特征。Adjuvant!Online考虑合并症，CancerMath显示年龄相关的非癌症死亡率。未报告治疗造成的伤害。20名女性参与了决策辅助工具的焦点小组试点测试，直至达到数据饱和。共有102名女性同意参与在线调查，其中86名完成了调查。正确回答率为90.5%，单个问题的回答率在84%至95%之间。
没有一种临床预测工具能够满足为女性提供所有必要信息以做出明智决策的要求。关于个体预后的信息得到了很好的理解，可以纳入患者决策辅助工具中。
