Ellen G. Engelhardt

Deciding about (neo-)adjuvant rectal and breast cancer treatment: Missed opportunities for shared decision making

Background. The first step in shared decision making (SDM) is creating choice awareness. This is particularly relevant in consultations concerning preference-sensitive treatment decisions, e.g. those addressing (neo-)adjuvant therapy. Awareness can be achieved by explicitly stating, as the ‘reason for encounter’, that a treatment decision needs to be made. It is unknown whether oncologists express such reason for encounter. This study aims to establish: 1) if ‘making a treatment decision’ is stated as a reason for the encounter and if not, what other reason for encounter is provided; and 2) whether mentioning that a treatment decision needs to be made is associated with enhanced patient involvement in decision making. Material and methods. Consecutive first consultations with: 1) radiation oncologists and rectal cancer patients; or 2) medical oncologists and breast cancer patients, facing a preference-sensitive treatment decision, were audiotaped. The tapes were transcribed and coded using an instrument developed for the study. Oncologists’ involvement of patients in decision making was coded using the OPTION-scale. Results. Oncologists (N = 33) gave a reason for encounter in 70/100 consultations, usually (N = 52/70, 74%) at the start of the consultation. The reason for encounter stated was ‘making a treatment decision’ in 3/100 consultations, and ‘explaining treatment details’ in 44/100 consultations. The option of foregoing adjuvant treatment was not explicitly presented in any consultation. Oncologist’ involvement of patients in decision making was below baseline (Md OPTION-score = 10). Given the small number of consultations in which the need to make a treatment decision was stated, we could not investigate the impact thereof on patient involvement. Conclusion. This study suggests that oncologists rarely express that a treatment decision needs to be made in consultations concerning preference-sensitive treatment decisions. Therefore, patients might not realize that foregoing (neo-)adjuvant treatment is a viable choice. Oncologists miss a crucial opportunity to facilitate SDM.

Breast cancer specialists' views on and use of risk prediction models in clinical practice: A mixed methods approach

Abstract Purpose. Risk prediction models (RPM) in breast cancer quantify survival benefit from adjuvant systemic treatment. These models [e.g. Adjuvant! Online (AO)] are increasingly used during consultations, despite their not being designed for such use. As still little is known about oncologists’ views on and use of RPM to communicate prognosis to patients, we investigated if, why, and how they use RPM. Methods. We disseminated an online questionnaire that was based on the literature and individual and group interviews with oncologists. Results. Fifty-one oncologists (partially) completed the questionnaire. AO is the best known (95%) and most frequently used RPM (96%). It is used to help oncologists decide whether or not to recommend chemotherapy (> 85%), to inform (86%) and help patients decide about treatment (> 80%), or to persuade them to follow the proposed course of treatment (74%). Most oncologists (74%) believe that using AO helps patients understand their prognosis. Conclusion. RPM have found a place in daily practice, especially AO. Oncologists think that using AO helps patients understand their prognosis, yet studies suggest that this is not always the case. Our findings highlight the importance of exploring whether patients understand the information that RPM provide.

Disclosing the Uncertainty Associated with Prognostic Estimates in Breast Cancer: Current Practices and Patients’ Perceptions of Uncertainty

Background. Treatment decision making is often guided by evidence-based probabilities, which may be presented to patients during consultations. These probabilities are intrinsically imperfect and embody 2 types of uncertainties: aleatory uncertainty arising from the unpredictability of future events and epistemic uncertainty arising from limitations in the reliability and accuracy of probability estimates. Risk communication experts have recommended disclosing uncertainty. We examined whether uncertainty was discussed during cancer consultations and whether and how patients perceived uncertainty. Methods. Consecutive patient consultations with medical oncologists discussing adjuvant treatment in early-stage breast cancer were audiotaped, transcribed, and coded. Patients were interviewed after the consultation to gain insight into their perceptions of uncertainty. Results. In total, 198 patients were included by 27 oncologists. Uncertainty was disclosed in 49% (97/197) of consultations. In those 97 consultations, 23 allusions to epistemic uncertainty were made and 84 allusions to aleatory uncertainty. Overall, the allusions to the precision of the probabilities were somewhat ambiguous. Interviewed patients mainly referred to aleatory uncertainty if not prompted about epistemic uncertainty. Even when specifically asked about epistemic uncertainty, 1 in 4 utterances referred to aleatory uncertainty. When talking about epistemic uncertainty, many patients contradicted themselves. In addition, 1 in 10 patients seemed not to realize that the probabilities communicated during the consultation are imperfect. Conclusions. Uncertainty is conveyed in only half of patient consultations. When uncertainty is communicated, oncologists mainly refer to aleatory uncertainty. This is also the type of uncertainty that most patients perceive and seem comfortable discussing. Given that it is increasingly common for clinicians to discuss outcome probabilities with their patients, guidance on whether and how to best communicate uncertainty is urgently needed.

Prediction models for patients with esophageal or gastric cancer: A systematic review and meta-analysis

Background Clinical prediction models are increasingly used to predict outcomes such as survival in cancer patients. The aim of this study was threefold. First, to perform a systematic review to identify available clinical prediction models for patients with esophageal and/or gastric cancer. Second, to evaluate sources of bias in the included studies. Third, to investigate the predictive performance of the prediction models using meta-analysis. Methods MEDLINE, EMBASE, PsycINFO, CINAHL, and The Cochrane Library were searched for publications from the year 2000 onwards. Studies describing models predicting survival, adverse events and/or health-related quality of life (HRQoL) for esophageal or gastric cancer patients were included. Potential sources of bias were assessed and a meta-analysis, pooled per prediction model, was performed on the discriminative abilities (c-indices). Results A total of 61 studies were included (45 development and 16 validation studies), describing 47 prediction models. Most models predicted survival after a curative resection. Nearly 75% of the studies exhibited bias in at least 3 areas and model calibration was rarely reported. The meta-analysis showed that the averaged c-index of the models is fair (0.75) and ranges from 0.65 to 0.85. Conclusion Most available prediction models only focus on survival after a curative resection, which is only relevant to a limited patient population. Few models predicted adverse events after resection, and none focused on patient’s HRQoL, despite its relevance. Generally, the quality of reporting is poor and external model validation is limited. We conclude that there is a need for prediction models that better meet patients’ information needs, and provide information on both the benefits and harms of the various treatment options in terms of survival, adverse events and HRQoL.

Oncologists’ weighing of the benefits and side effects of adjuvant systemic therapy: Has it changed over time?

The use of adjuvant chemotherapy and endocrine therapy for early stage breast cancer has substan-tially increased. The presentation of the Early Breast Cancer Trialists Collaborative Group (EBCTCG) meta-analyses of adjuvant systemic treatment effec-tiveness, late 1990s, led to a paradigm shift where adjuvant systemic treatment was no longer reserved for patients with (locally) advanced disease, but also became available to node negative patients [1]. New insights in prognostic factors and improvements in treatment have led to further easing of the eligibility criteria for adjuvant systemic treatment over time. For example, according to the American National Comprehensive Cancer Network (NCCN) breast cancer guidelines, some form of adjuvant systemic treatment could be considered for all breast cancer patients with invasive ductal or lobular tumors larger than 0.5 cm. If a patient has Her2-positive disease, adjuvant systemic treatment could also be consid-ered for tumors smaller than 0.5 cm [2]. Going by these NCCN and other (inter)national guidelines, a proportion of early stage breast cancer patients with a clinical indication for adjuvant systemic treatment have a potential overall survival benefi t of as little as 1% – conversely, 99% of these patients potentially only experience side effects and no survival gain. With the exception of patient subgroups deemed at high risk of recurrence and breast cancer mortality (e.g. Her2-positive patients or those 40 years or younger at diagnosis), the general rule of thumb applied in the Netherlands is that adjuvant systemic treatment is advised if treatment reduces the patient ’ s risk of breast cancer death by at least 4% (absolute). This easing of the eligibility criteria for adjuvant sys-temic treatment is also refl ected in the substantial increase in its use in Dutch clinical practice from 1990 – 2011. Whereas between 1990 and 1997 only 37% of early stage breast cancer patients received adjuvant systemic therapy, in 2011 an average of 70% of early stage breast patients received adjuvant systemic treatment [3,4]. In 2000, just after the pub-lication of the fi rst EBCTCG meta-analysis, a sur-vey amongst Dutch oncologists reported that the majority felt that adjuvant chemotherapy should minimally yield 6 – 10% overall survival benefi t to make it worthwhile for patients with node negative disease [5]. To date no studies have assessed what survival benefi t makes endocrine treatment worth-while according to oncologists. Yet, endocrine treat-ment duration has been extended more and more (from 2.5 to 5 years and an extension to 10 years is currently topic of debate), whilst studies show non-adherence and/or premature discontinuation of treatment of as much as 40% [6 – 8]. It has been over a decade since Stiggelbout et al. conducted their survey of oncologists ’ views on the survival benefi t that makes adjuvant chemotherapy