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Background: Comprehensive genomic profiling (CGP) can identify targets beyond standard of care, potentially revolutionizing personalized cancer management. However, conducting well designed studies in this rapidly evolving field is complex and demands time and investments. Consequently, the total added value of CGP remains uncertain. Clinical benefit and costs often are driving factors in coverage decisions. Recently, five additional factors were identified in the literature that can influence the choice for targeted profiling vs. CGP, specifically: "feasibility", "test journey patient/physician", "wider implications of diagnostic results", "organization of laboratories", and "scientific spillover". The objective of the current study is to examine the role and importance assigned to these five additional factors for a comprehensive technology assessment by different stakeholders., Methods: Purposive sampling was used to identify respondents from 4 stakeholder groups (i.e., medical specialists, molecular specialists, patient representatives, and policymakers) from different regions and hospital types (academic vs. non-academic) in the Netherlands. In semi-structured interviews, respondents scored the importance to decision-making of the five factors on a 0 (not important) to 5 (essential) scale. Reasoning behind the scores were elicited using open-ended follow-up questions. Transcripts were independently double-coded by two researchers using thematic analysis., Results: Nineteen stakeholders (100% response rate; medical specialists (n = 7), molecular specialists (n = 7), patient representatives (n = 2), and policymakers (n = 3)) were interviewed. We observed differences between stakeholders in the relative importance assigned to the factors (range of median importance scores: 2-5). Overall, "wider implications of diagnostic results", primarily CGP's potential to identify additional treatment options, was deemed the most important factor alongside clinical benefit and costs in decision-making about CGP (median range: 3-5). While the "organization of laboratories" was considered less important (median range: 3-4), opposing arguments and preferences regarding the organization of laboratories were identified, with participants from academic centers preferring a centralized approach whilst non-academics preferred a decentralized approach., Conclusions: Stakeholders deemed "wider implications of diagnostic results", "feasibility", and "test journey" the most important considerations for decision-making about targeted profiling vs. CGP alongside clinical benefit and costs. For policy decision-making, it is important to understand the arguments behind the heterogeneous opinions, often related to the setting they originate from., Competing Interests: Declarations. Ethics approval and consent to participate: All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Institutional Review Board of the Antoni van Leeuwenhoek hospital (IRBd23-111). Informed consent was obtained from all individual participants included in the study. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Introduction: Risk prediction models (RPM) can help soft-tissue sarcoma(STS) patients and clinicians make informed treatment decisions by providing them with estimates of (disease-free) survival for different treatment options. However, it is unknown how RPMs are used in the clinical encounter to support decision-making. This study aimed to understand how a PERsonalised SARcoma Care (PERSARC) RPM is used to support treatment decisions and which barriers and facilitators influence its use in daily clinical practice., Methods: A convergent mixed-methods design is used to understand how PERSARC is integrated in the clinical encounter in three Dutch sarcoma centers. Data were collected using qualitative interviews with STS patients (n = 15) and clinicians (n = 8), quantitative surveys (n = 50) and audiotaped consultations (n = 30). Qualitative data were analyzed using thematic analysis and integrated with quantitative data through merging guided by the SEIPS model., Results: PERSARC was generally used to support clinicians' proposed treatment plan and not to help patients weigh available treatment options. Use of PERSARC in decision-making was hampered by clinician's doubts about whether there were multiple viable treatment options,the accuracy of risk estimates, and time constraints. On the other hand, use of PERSARC facilitated clinicians to estimate and communicate the expected benefit of adjuvant therapy to patients., Conclusion: PERSARC was not used to support informed treatment decision-making in STS patients. Integrating RPMs into clinical consultations requires acknowledgement of their benefits in facilitating clinicians' estimation of the expected benefit of adjuvant therapies and information provision to patients, while also considering concerns regarding RPM quality and treatment options' viability., Competing Interests: Declaration of Competing Interest The authors declare no conflicts of interest., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Ductal carcinoma in situ (DCIS) can progress to invasive breast cancer (IBC), but often never will. As we cannot predict accurately which DCIS-lesions will or will not progress to IBC, almost all women with DCIS undergo breast-conserving surgery supplemented with radiotherapy, or even mastectomy. In some countries, endocrine treatment is prescribed as well. This implies many women with non-progressive DCIS undergo overtreatment. To reduce this, the LORD patient preference trial (LORD-PPT) tests whether mammographic active surveillance (AS) is safe by giving women with low-risk DCIS a choice between treatment and AS. For this, sufficient knowledge about DCIS is crucial. Therefore, we assessed women's DCIS knowledge in association with socio-demographic and clinical characteristics., Methods: LORD-PPT participants (N = 376) completed a questionnaire assessing socio-demographic and clinical characteristics, risk perception, treatment choice and DCIS knowledge after being informed about their diagnosis and treatment options., Results: 66 % of participants had poor knowledge (i.e., answered ≤3 out of 7 knowledge items correctly). Most incorrect answers involved overestimating the safety of AS and misunderstanding of DCIS prognostic risks. Overall, women with higher DCIS knowledge score perceived their risk of developing IBC as being somewhat higher than women with poorer knowledge (p = 0.049). Women with better DCIS knowledge more often chose surgery whilst most women with poorer knowledge chose active surveillance (p = 0.049)., Discussion: Our findings show that there is room for improvement of information provision to patients. Decision support tools for patients and clinicians could help to stimulate effective shared decision-making about DCIS management., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Comprehensive Genomic Profiling (CGP) allows for the identification of many targets. Reimbursement decision-making is, however, challenging because besides the health benefits of on-label treatments and costs, other factors related to diagnostic and treatment pathways may also play a role. The aim of this study was to identify which other factors are relevant for the technology assessment of CGP and to summarize the available evidence for these factors. After a scoping search and two expert sessions, five factors were identified: feasibility, test journey, wider implications of diagnostic results, organisation of laboratories, and "scientific spillover". Subsequently, a systematic search identified 83 studies collecting mainly evidence for the factors "test journey" and "wider implications of diagnostic results". Its nature was, however, of limited value for decision-making. We recommend the use of comparative strategies, uniformity in outcome definitions, and the inclusion of a comprehensive set of factors in future evidence generation., Competing Interests: Declaration of Competing Interest L.F. van Schaik, E.G. Engelhardt, E.A. Wilthagen, A. Fernández Coves, M.A. Joore, W.H. van Harten and V.P. Retèl declare no competing interests. N. Steeghs provided consultation or attended advisory boards for Boehringer Ingelheim, Ellipses Pharma, GlaxoSmithKline, Incyte, Luszana. N Steeghs received research grants from Abbvie, Actuate Therapeutics, Amgen, Array, Ascendis Pharma, AstraZeneca, Bayer, Blueprint Medicines, Boehringer Ingelheim, Bristol-Myers Squibb, Cantargia, CellCentric, Cogent Biosciences, Cresecendo Biologics, Cytovation, Deciphera, Dragonfly, Eli Lilly, Exelixis, Genentech, GlaxoSmithKline, IDRx, Immunocore, Incyte, InteRNA, Janssen, Kinnate Biopharma, Kling Biotherapeutics, Lixte, Luszana, Merck, Merck Sharp & Dohme, Merus, Molecular Partners, Navire Pharma, Novartis, Numab Therapeutics, Pfizer, Relay Pharmaceuticals, Revolution Medicin, Roche, Sanofi, Seattle Genetics, Taiho, Takeda. All outside the submitted work, all payment to the Netherlands Cancer Institute., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: If communicated adequately, numerical decision-relevant information can support informed and shared decision making. Visual formats are recommended, but which format supports patients depending on their health literacy (HL) levels for specific decisions is unclear., Study Aim: The aim of this study is to investigate: 1) the effect of survival rates and side-effects presentation formats on comprehension and 'feeling informed'; 2) differential effects among women with higher/lower HL, with adjuvant systemic breast cancer therapy as case example., Methods: Two online experiments among women from the Dutch population without a history of breast cancer were conducted. Experiment 1 had a 3 (survival rate format: text block-bar graph-icon array) x 2 (HL: low-high) between-subjects design. Experiment 2 had a 5 (side-effects format: no probability information-probability information in numbers with or without a visualisation-probability information in numbers with or without a visualisation accompanied by a description of the side-effects) x 2 (HL: low-high) design. Primary outcomes were comprehension and feeling informed (Experiment 2 only). Formats were previously designed in co-creation with patients., Results: In Experiment 1, presentation format did not affect gist or verbatim comprehension. Higher HL was associated with higher gist comprehension. Experiment 2 showed an interaction between presentation format and HL on 'feeling informed'. When provided with visualised probability information without a description of the side-effects, women with lower HL felt better informed than women with higher HL., Conclusion: Visual formats did not enhance comprehension of survival rate information beyond a well-designed text block format. However, none of the formats could overcome HL differences. When designing decision-relevant information, visualisations might not necessarily provide an advantage over structured numerical information for both patients with lower and higher HL. However, a deeper understanding of presenting side-effect information is warranted., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 van Strien-Knippenberg et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Purpose: To assess information and communication priorities of patients and healthcare professionals in Shared Decision Making about adjuvant systemic treatment of primary breast cancer and identify key decision-relevant information accordingly., Methods: Patients (N = 122) and professionals working with breast cancer patients (N = 118), of whom 38 were nurse practitioners and 32 nurses, were recruited using convenience sampling, and surveyed about information/communication aspects key to decision-making, using ranking assignments. We further posed a simple open question, questions about receiving population-based statistics versus personalized statistics concerning treatment outcomes, and their attitude and experience concerning Shared Decision Making. Data were analyzed using descriptive analysis and a qualitative analysis., Results: Both patients and professionals prioritized information about treatment outcomes (i.e., survival, recurrence) as key decision-relevant information for patients. Patients prioritized information about relatively severe treatment side-effects and late effects (e.g., blood clot, stroke), whilst professionals prioritized information about effects that occur relatively often (e.g., hair loss, fatigue). Patients specifically wanted to know if the benefit of treatment is worth the negative impact. Both groups prioritized personalized statistics over population-based statistics., Conclusions: Some differences between patients and professionals were found in information and communication priorities, specifically related to the different side-effects. It seems worthwhile to precisely address these side-effects in Shared Decision Making concerning adjuvant systemic treatment. Furthermore, it seems important to deliberate together on the question if expected benefit of treatment is worth the potential negative impact for the individual patient., Competing Interests: Declaration of competing interest Domino Determann was working at ‘PATIENT+’ at the time of the study. PATIENT+ is part of the larger consortium; it is a company that provides the patient decision support tool for breast cancer adjuvant therapy that was studied (https://patientplus.info/). The other authors have no competing interests to declare., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: To improve Shared decision-making (SDM) regarding personalized post-treatment surveillance, the Breast Cancer Surveillance Decision Aid (BCS-PtDA), integrating personalized risk information, was developed and implemented in eight hospitals. The aim of this mixed-methods study was to (1) assess the implementation and participation rates, (2) identify facilitators and barriers for use by health care professionals (HCPs), (3) quantify the observed level of SDM, and (4) evaluate risk communication and SDM application in consultations., Methods: Implementation and participation rates and patients' BCS-PtDA use were calculated using hospital registry data and BCS-PtDA log data. HCPs' perspective on facilitators and barriers were collected using the MIDI framework. Observed SDM levels in consultation transcripts were quantified using the OPTION-5 scale. Thematic analysis was performed to assess consultation content., Results: The average PtDA implementation and participation rates were, respectively, 26% and 61%. HCPs reported that the PtDA supported choice awareness. Reported barriers for implementation were mainly increased workload and a lack of perceived benefits. The consultation analysis ( n = 64) showed patients were offered a choice, but deliberation was lacking. Risk communication was generally adequate., Discussion: When the BCS-PtDA was used, patients were clearly given a choice regarding their post-treatment surveillance, but information provision and SDM application can be improved.

Introduction: Current treatment decision-making in high-grade soft-tissue sarcoma (STS) care is not informed by individualised risks for different treatment options and patients' preferences. Risk prediction tools may provide patients and professionals insight in personalised risks and benefits for different treatment options and thereby potentially increase patients' knowledge and reduce decisional conflict. The VALUE-PERSARC study aims to assess the (cost-)effectiveness of a personalised risk assessment tool (PERSARC) to increase patients' knowledge about risks and benefits of treatment options and to reduce decisional conflict in comparison with usual care in high-grade extremity STS patients., Methods: The VALUE-PERSARC study is a parallel cluster randomised control trial that aims to include at least 120 primarily diagnosed high-grade extremity STS patients in 6 Dutch hospitals. Eligible patients (≥18 years) are those without a treatment plan and treated with curative intent. Patients with sarcoma subtypes or treatment options not mentioned in PERSARC are unable to participate. Hospitals will be randomised between usual care (control) or care with the use of PERSARC (intervention). In the intervention condition, PERSARC will be used by STS professionals in multidisciplinary tumour boards to guide treatment advice and in patient consultations, where the oncological/orthopaedic surgeon informs the patient about his/her diagnosis and discusses benefits and harms of all relevant treatment options. The primary outcomes are patients' knowledge about risks and benefits of treatment options and decisional conflict (Decisional Conflict Scale) 1 week after the treatment decision has been made. Secondary outcomes will be evaluated using questionnaires, 1 week and 3, 6 and 12 months after the treatment decision. Data will be analysed following an intention-to-treat approach using a linear mixed model and taking into account clustering of patients within hospitals., Ethics and Dissemination: The Medical Ethical Committee Leiden-Den Haag-Delft (METC-LDD) approved this protocol (NL76563.058.21). The results of this study will be reported in a peer-review journal., Trial Registration Number: NL9160, NCT05741944., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Ductal carcinoma in situ (DCIS) can progress to invasive breast cancer (IBC), but most DCIS lesions remain indolent. However, guidelines recommend surgery, often supplemented by radiotherapy. This implies overtreatment of indolent DCIS. The non-randomised patient preference LORD-trial tests whether active surveillance (AS) for low-risk DCIS is safe, by giving women with low-risk DCIS a choice between AS and conventional treatment (CT). Here, we aim to describe how participants are distributed among both trial arms, identify their motives for their preference, and assess factors associated with their choice., Methods: Data were extracted from baseline questionnaires. Descriptive statistics were used to assess the distribution and characteristics of participants; thematic analyses to extract self-reported reasons for the choice of trial arm, and multivariable logistic regression analyses to investigate associations between patient characteristics and chosen trial arm., Results: Of 377 women included, 76% chose AS and 24% CT. Most frequently cited reasons for AS were "treatment is not (yet) necessary" (59%) and trust in the AS-plan (39%). Reasons for CT were cancer worry (51%) and perceived certainty (29%). Women opting for AS more often had lower educational levels (OR 0.45; 95% confidence interval [CI], 0.22-0.93) and more often reported experiencing shared decision making (OR 2.71; 95% CI, 1.37-5.37) than women choosing CT., Conclusion: The LORD-trial is the first to offer women with low-risk DCIS a choice between CT and AS. Most women opted for AS and reported high levels of trust in the safety of AS. Their preferences highlight the necessity to establish the safety of AS for low-risk DCIS., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Purpose: Neoadjuvant systemic therapy (NST) is increasingly used in breast cancer patients and depending on subtype, 10-89% of patients will attain pathologic complete response (pCR). In patients with pCR, risk of local recurrence (LR) after breast conserving therapy is low. Although adjuvant radiotherapy after breast conserving surgery (BCS) reduces LR further in these patients, it may not contribute to overall survival. However, radiotherapy may cause early and late toxicity. The aim of this study is to show that omission of adjuvant radiotherapy in patients with a pCR after NST will result in acceptable low LR rates and good quality of life., Methods: The DESCARTES study is a prospective, multicenter, single arm study. Radiotherapy will be omitted in cT1-2N0 patients (all subtypes) who achieve a pCR of the breast and lymph nodes after NST followed by BCS plus sentinel node procedure. A pCR is defined as ypT0N0 (i.e. no residual tumor cells detected). Primary endpoint is the 5-year LR rate, which is expected to be 4% and deemed acceptable if less than 6%. In total, 595 patients are needed to achieve a power of 80% (one-side alpha of 0.05). Secondary outcomes include quality of life, Cancer Worry Scale, disease specific and overall survival. Projected accrual is five years., Conclusion: This study bridges the knowledge gap regarding LR rates when adjuvant radiotherapy is omitted in cT1-2N0 patients achieving pCR after NST. If the results are positive, radiotherapy may be safely omitted in selected breast cancer patients with a pCR after NST., Trial Registration: This study is registered at ClinicalTrials.gov on June 13th 2022 (NCT05416164). Protocol version 5.1 (15-03-2022)., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Women with a BRCA1/2 pathogenic variant are advised to undergo premenopausal risk-reducing salpingo-oophorectomy after completion of childbearing, to reduce their risk of ovarian cancer. Several studies reported less sexual pleasure 1 to 3 years after a premenopausal oophorectomy. However, the long-term effects of premenopausal oophorectomy on sexual functioning are unknown., Objective: This study aimed to study long-term sexual functioning in women at increased familial risk of breast or ovarian cancer who underwent a risk-reducing salpingo-oophorectomy either before the age of 46 years (premenopausal group) or after the age of 54 years (postmenopausal group). Subgroup analyses were performed in the premenopausal group, comparing early (before the age of 41 years) and later (at ages 41-45 years) premenopausal risk-reducing salpingo-oophorectomy., Study Design: Between 2018 and 2021, 817 women with a high familial risk of breast or ovarian cancer from an ongoing cohort study were invited to participate in our study. Because of a large difference in age in the study between the premenopausal and postmenopausal salpingo-oophorectomy groups, we restricted the comparison of sexual functioning between the groups to 368 women who were 60 to 70 years old at completion of the questionnaire (226 in the premenopausal group and 142 in the postmenopausal group). In 496 women with a premenopausal risk-reducing salpingo-oophorectomy, we compared the sexual functioning between women in the early premenopausal group (n=151) and women in the later premenopausal group (n=345). Differences between groups were analyzed using multiple regression analyses, adjusting for current age, breast cancer history, use of hormone replacement therapy, body mass index, chronic medication use (yes or no), and body image., Results: Mean times since risk-reducing salpingo-oophorectomy were 20.6 years in the premenopausal group and 10.6 years in the postmenopausal group (P<.001). The mean age at questionnaire completion was 62.7 years in the premenopausal group, compared with 67.0 years in the postmenopausal group (P<.001). Compared with 48.9% of women in the postmenopausal group, 47.4% of women in the premenopausal group were still sexually active (P=.80). Current sexual pleasure scores were the same for women in the premenopausal group and women in the postmenopausal group (mean pleasure score, 8.6; P=.99). However, women in the premenopausal group more often reported substantial discomfort than women in the postmenopausal group (35.6% vs 20.9%; P=.04). After adjusting for confounders, premenopausal risk-reducing salpingo-oophorectomy was associated with substantially more discomfort during sexual intercourse than postmenopausal risk-reducing salpingo-oophorectomy (odds ratio, 3.1; 95% confidence interval, 1.04-9.4). Moreover, after premenopausal risk-reducing salpingo-oophorectomy, more severe complaints of vaginal dryness were observed (odds ratio, 2.6; 95% confidence interval, 1.4-4.7). Women with a risk-reducing salpingo-oophorectomy before the age of 41 years reported similar pleasure and discomfort scores as women with a risk-reducing salpingo-oophorectomy between ages 41 and 45 years., Conclusion: More than 15 years after premenopausal risk-reducing salpingo-oophorectomy, the proportion of sexually active women was comparable with the proportion of sexually active women with a postmenopausal risk-reducing salpingo-oophorectomy. However, after a premenopausal risk-reducing salpingo-oophorectomy, women experienced more vaginal dryness and more often had substantial sexual discomfort during sexual intercourse. This did not lead to less pleasure with sexual activity., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Objectives: In patients with an ovarian mass, a risk of malignancy assessment is used to decide whether referral to an oncology hospital is indicated. Risk assessment strategies do not perform optimally, resulting in either referral of patients with a benign mass or patients with a malignant mass not being referred. This process may affect the psychological well-being of patients. We evaluated cancer-specific distress during work-up for an ovarian mass, and patients' perceptions during work-up, referral, and treatment., Methods: Patients with an ovarian mass scheduled for surgery were enrolled. Using questionnaires we measured (1) cancer-specific distress using the cancer worry scale, (2) patients' preferences regarding referral (evaluated pre-operatively), and (3) patients' experiences with work-up and treatment (evaluated post-operatively). A cancer worry scale score of ≥14 was considered as clinically significant cancer-specific distress., Results: A total of 417 patients were included, of whom 220 (53%) were treated at a general hospital and 197 (47%) at an oncology hospital. Overall, 57% had a cancer worry scale score of ≥14 and this was higher in referred patients (69%) than in patients treated at a general hospital (43%). 53% of the patients stated that the cancer risk should not be higher than 25% to undergo surgery at a general hospital. 96% of all patients were satisfied with the overall work-up and treatment. No difference in satisfaction was observed between patients correctly (not) referred and patients incorrectly (not) referred., Conclusions: Relatively many patients with an ovarian mass experienced high cancer-specific distress during work-up. Nevertheless, patients were satisfied with the treatment, regardless of the final diagnosis and the location of treatment. Moreover, patients preferred to be referred even if there was only a relatively low probability of having ovarian cancer. Patients' preferences should be taken into account when deciding on optimal cut-offs for risk assessment strategies., Competing Interests: Competing interests: None declared., (© IGCS and ESGO 2022. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Clinical prediction models are often not evaluated properly in specific settings or updated, for instance, with information from new markers. These key steps are needed such that models are fit for purpose and remain relevant in the long-term. We aimed to present an overview of methodological guidance for the evaluation (i.e., validation and impact assessment) and updating of clinical prediction models., Methods: We systematically searched nine databases from January 2000 to January 2022 for articles in English with methodological recommendations for the post-derivation stages of interest. Qualitative analysis was used to summarize the 70 selected guidance papers., Results: Key aspects for validation are the assessment of statistical performance using measures for discrimination (e.g., C-statistic) and calibration (e.g., calibration-in-the-large and calibration slope). For assessing impact or usefulness in clinical decision-making, recent papers advise using decision-analytic measures (e.g., the Net Benefit) over simplistic classification measures that ignore clinical consequences (e.g., accuracy, overall Net Reclassification Index). Commonly recommended methods for model updating are recalibration (i.e., adjustment of intercept or baseline hazard and/or slope), revision (i.e., re-estimation of individual predictor effects), and extension (i.e., addition of new markers). Additional methodological guidance is needed for newer types of updating (e.g., meta-model and dynamic updating) and machine learning-based models., Conclusion: Substantial guidance was found for model evaluation and more conventional updating of regression-based models. An important development in model evaluation is the introduction of a decision-analytic framework for assessing clinical usefulness. Consensus is emerging on methods for model updating., (© 2022. The Author(s).)

Even though Ductal Carcinoma in Situ (DCIS) can potentially be an invasive breast cancer (IBC) precursor, most DCIS lesions never will progress to IBC if left untreated. Because we cannot predict yet which DCIS lesions will and which will not progress, almost all women with DCIS are treated by breast-conserving surgery +/- radiotherapy, or even mastectomy. As a consequence, many women with non-progressive DCIS carry the burden of intensive treatment without any benefit. Multiple decision support tools have been developed to optimize DCIS management, aiming to find the balance between over- and undertreatment. In this systematic review, we evaluated the quality and added value of such tools. A systematic literature search was performed in Medline(ovid), Embase(ovid), Scopus and TRIP. Following the PRISMA guidelines, publications were selected. The CHARMS (prediction models) or IPDAS (decision aids) checklist were used to evaluate the tools' methodological quality. Thirty-three publications describing four decision aids and six prediction models were included. The decision aids met at least 50% of the IPDAS criteria. However, most lacked tools to facilitate discussion of the information with healthcare providers. Five prediction models quantify the risk of an ipsilateral breast event after a primary DCIS, one estimates the risk of contralateral breast cancer, and none included active surveillance. Good quality and external validations were lacking for all prediction models. There remains an unmet clinical need for well-validated, good-quality DCIS risk prediction models and decision aids in which active surveillance is included as a management option for low-risk DCIS.

Background: Non-genetic healthcare professionals can provide pre-test counseling and order germline genetic tests themselves, which is called mainstream genetic testing. In this systematic review, we determined whether mainstream genetic testing was feasible in daily practice while maintaining quality of genetic care., Methods: PubMed, Embase, CINAHL, and PsychINFO were searched for articles describing mainstream genetic testing initiatives in cancer care., Results: Seventeen articles, reporting on 15 studies, met the inclusion criteria. Non-genetic healthcare professionals concluded that mainstream genetic testing was possible within the timeframe of a routine consultation. In 14 studies, non-genetic healthcare professionals completed some form of training about genetics. When referral was coordinated by a genetics team, the majority of patients carrying a pathogenic variant were seen for post-test counseling by genetic healthcare professionals. The number of days between cancer diagnosis and test result disclosure was always lower in the mainstream genetic testing pathway than in the standard genetic testing pathway (e.g., pre-test counseling at genetics department)., Conclusions: Mainstream genetic testing seems feasible in daily practice with no insurmountable barriers. A structured pathway with a training procedure is desirable, as well as a close collaboration between genetics and other clinical departments.

Total mesorectal excision for rectal cancer is a major operation associated with morbidity and mortality. For older or inoperable patients, alternatives are necessary. This prospective study evaluated the oncological and functional outcome and quality of life of older or inoperable rectal cancer patients treated with a contact X-ray brachytherapy boost to avoid major surgery. During follow-up, tumor response and toxicity on endoscopy were scored. Functional outcome and quality of life were assessed with self-administered questionnaires. Additionally, in-depth interviews regarding patients' experiences were conducted. Nineteen patients were included with a median age of 80 years (range 72-91); nine patients achieved a clinical complete response and in another four local control of the tumor was established. The 12 month organ-preservation rate, progression-free survival, and overall survival were 88%, 78%, and 100%, respectively. A transient decrease in quality of life and bowel function was observed at 3 months, which was generally restored at 6 months. In-depth interviews revealed that patients' experience was positive despite the side-effects shortly after treatment. In older or inoperable rectal cancer patients, contact X-ray brachytherapy can be considered an option to avoid total mesorectal excision. Contact X-ray brachytherapy is well-tolerated and can provide good tumor control.

As ongoing trials study the safety of an active surveillance strategy for low-risk ductal carcinoma in situ (DCIS), there is a need to explain why particular choices regarding treatment strategies are made by eligible women as well as their oncologists, what factors enter the decision process, and how much each factor affects their choice. To measure preferences for treatment and surveillance strategies, women with newly-diagnosed, primary low-risk DCIS enrolled in the Dutch CONTROL DCIS Registration and LORD trial, and oncologists participating in the Dutch Health Professionals Study were invited to complete a discrete choice experiment (DCE). The relative importance of treatment strategy-related attributes (locoregional intervention, 10-year risk of ipsilateral invasive breast cancer (iIBC), and follow-up interval) were discerned using conditional logit models. A total of n = 172 patients and n = 30 oncologists completed the DCE. Patient respondents had very strong preferences for an active surveillance strategy with no surgery, irrespective of the 10-year risk of iIBC. Extensiveness of the locoregional treatment was consistently shown to be an important factor for patients and oncologists in deciding upon treatment strategies. Risk of iIBC was least important to patients and most important to oncologists. There was a stronger inclination toward a twice-yearly follow-up for both groups compared to annual follow-up.

Treatment decision-making for patients with incurable non-small cell lung cancer (NSCLC) is complex due to the rapidly increasing number of treatments and discovery of new biomarkers. Decision support systems (DSS) could assist thoracic oncologists (TO) weighing of the pros and cons of treatments in order to arrive at an evidence-based and personalized treatment advice. Our aim is to inventory (1) TO's needs with regard to DSS in the treatment of incurable (stage IIIB/IV) NSCLC patients, and (2) preferences regarding the development of future tools in this field. We disseminated an online inventory questionnaire among all members of the Section of Oncology within the Society of Physicians in Chest Medicine and Tuberculosis. Telephone interviews were conducted to better contextualize the findings from the questionnaire. In total, 58 TO completed the questionnaire and expressed a need for new DSS. They reported that it is important for tools to include genetic and immune markers, to be sufficiently validated, regularly updated, and time-efficient. Also, future DSS should incorporate multiple treatment options, integrate estimates of toxicity, quality of life and cost-effectiveness of treatments, enhance communication between caregivers and patients, and use IT solutions for a clear interface and continuous updating of tools. With this inventory among Dutch TO, we summarized the need for new DSS to aid treatment decision-making for patients with incurable NSCLC. To meet the expressed needs, substantial additional efforts will be required by DSS developers, above already existing tools.

Objective: The majority of 'low-risk' (grade I/II) Ductal Carcinoma In Situ (DCIS) may not progress to invasive breast cancer during a women's lifetime. Therefore, the safety of active surveillance versus standard surgical treatment for DCIS is prospectively being evaluated in clinical trials. If proven safe and selectively implemented in clinical practice, a significant group of women with low-risk DCIS may forego surgery and radiotherapy in the future. Identification of modifiable and non-modifiable risk factors associated with prognosis after a primary DCIS would also enhance our care of women with low-risk DCIS., Methods: To identify modifiable and non-modifiable risk factors for subsequent breast events after DCIS, we performed a systematic literature search in PUBMED, EMBASE and Scopus., Results: Six out of the 3870 articles retrieved were included for final data extraction. These six studies included a total of 4950 patients with primary DCIS and 640 recorded subsequent breast events. There was moderate evidence for an association of a family history of breast cancer, premenopausal status, high BMI, and high breast density with a subsequent breast cancer or further DCIS., Conclusion: There is a limited number of recent studies published on the impact of modifiable and non-modifiable risk factors on subsequent events after DCIS. The available evidence is insufficient to identify potential targets for risk reduction strategies, reflecting the relatively small numbers and the lack of long-term follow-up in DCIS, a low-event condition., Competing Interests: Declaration of competing interest None declared., (Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Purpose: Cancer-related cognitive problems (cancer-related cognitive problems) in working cancer survivors are found to affect work outcomes. We aimed to generate in-depth information regarding cancer-related cognitive problems in working cancer survivors, strategies used to cope with cancer-related cognitive problems at work, and needs of cancer survivors and professionals regarding cancer-related cognitive problems at work., Methods: Five focus groups were formed, amongst which three focus groups with cancer survivors (n = 8, n = 7, and n = 8) and two focus groups with professionals (n = 7, n = 8). Thematic analysis of the transcripts was performed to create concepts., Results: Both cancer survivors and professionals confirmed that cancer-related cognitive problems, which occurred in several domains of neurocognitive functioning, affect work functioning. Cancer survivors used several strategies (e.g., applying practical adjustments, re-organization of work, and accepting limitations) to cope with cancer-related cognitive problems at work, as did professionals in their attempt at supporting cancer survivors facing these problems. Various needs of cancer survivors (e.g., supportive care options, acknowledgment by others) and professionals (e.g., improvement of expertise, clarity about referral pathways) regarding cancer-related cognitive problems at work were mentioned., Conclusions: Due to the growing number of working cancer survivors dealing with cancer-related cognitive problems, it is essential to sustain their employability. Therefore, cognitive rehabilitation interventions should be developed, taking functioning at work into account. Knowledge amongst professionals regarding cancer-related cognitive problems, as well as coordination of care for cancer-related cognitive problems, should be improved. Ensuring professional education regarding cancer-related cognitive problems, within both the healthcare and occupational setting, is of utmost importance., Implications for Cancer Survivors: Support for working cancer survivors who experience cancer-related cognitive problems might increase their employability in the longer term.

Background . Adjuvant systemic treatment for early stage breast cancer significantly reduces the risk of mortality but is associated with side effects, reducing patients' quality of life. Decisions about adjuvant treatment are preference sensitive and are thus ideally suited to a shared decision making (SDM) approach. Whether and how SDM affects patients' trust in their oncologist is currently unknown. We investigated the association between patients' trust in their oncologist and 1) observed level of SDM in the consultation, 2) congruence between patients' preferred and perceived level of participation, and 3) patient and oncologist characteristics. Methods . Decision consultations ( n = 101) between breast cancer patients and their medical oncologist were audio-recorded and transcribed verbatim. Patients' trust in their oncologist was measured using the Trust in Oncologist Scale (TiOS). The observed level of SDM was scored using the 12-item Observing Patient Involvement In Decision Making scale (OPTION-12), preferred level of participation with the Control Preferences Scale, and perceived level of participation with an open question in telephonic interviews. Results . The average TiOS score was high overall (mean [SD] = 4.1 [.56]; range, 2.6-5.0). Low levels of SDM were observed (mean [SD] = 16 [11.6]; range, 2-56). Neither observed nor perceived level of participation in SDM was associated with trust. Patients' preferred and perceived role in decision making was incongruent in almost 50% of treatment decisions. Congruence was not related to trust. A larger tumor size (β = 4.5, P = 0.03) and the use of a risk prediction model during the consultation (β = 4.1, P = 0.04) were associated with stronger trust. Conclusion . Patients reported strong trust in their oncologist. While low levels of SDM were observed, SDM was not associated with trust. These findings suggest it may not be necessary to worry about negative consequences for trust of using SDM or risk prediction models in oncological consultations. Considering the increased emphasis on implementing SDM, it is important to further explore how SDM affects trust in clinical practice.

Background: Systemic treatment for advanced cancer offers uncertain and sometimes limited benefit, while the burden can be high. This study examines the effect of shared decision-making (SDM) training for medical oncologists on observed SDM in standardized patient assessments., Materials and Methods: A randomized controlled trial comparing training with standard practice was conducted. Medical oncologists and oncologists-in-training ( n  = 31) participated in a video-recorded, standardized patient assessment at baseline (T0) and after 4 months (T1, after training). The training was based on a four-stage SDM model and consisted of a reader, two group sessions (3.5 hours each), a booster session (1.5 hours), and a consultation card. The primary outcome was observed SDM as assessed with the Observing Patient Involvement scale (OPTION12) coded by observers blinded for arm. Secondary outcomes were observed SDM per stage, communication skills, and oncologists' satisfaction with communication., Results: The training had a significant and large effect on observed SDM in the simulated consultations (Cohen's f = 0.62) and improved observed SDM behavior in all four SDM stages (f = 0.39-0.72). The training improved oncologists' information provision skills (f = 0.77), skills related to anticipating/responding to emotions (f = 0.42), and their satisfaction with the consultation (f = 0.53)., Conclusion: Training medical oncologists in SDM about palliative systemic treatment improves their performance in simulated consultations. The next step is to examine the effect of such training on SDM in clinical practice and on patient outcomes., Implications for Practice: Systemic treatment for advanced cancer offers uncertain and sometimes limited benefit, while the burden can be high. Hence, applying the premises of shared decision-making (SDM) is recommended. SDM is increasingly advocated based on the ethical imperative to provide patient-centered care and the increasing evidence for beneficial patient outcomes. Few studies examined the effectiveness of SDM training in robust designs. This randomized controlled trial demonstrated that SDM training (10 hours) improves oncologists' performance in consultations with standardized patients. The next step is to examine the effect of training on oncologists' performance and patient outcomes in clinical practice., Competing Interests: Disclosures of potential conflicts of interest may be found at the end of this article., (© AlphaMed Press 2018.)

Background: Decision-making about palliative care for metastatic colorectal cancer (mCRC) consists of many different treatment-related decisions, and there generally is no best treatment option. Decision support systems (DSS), e.g., prognostic calculators, can aid oncologists' decision-making. DSS that contain features tailored to the needs of oncologists are more likely to be implemented in clinical practice. Therefore, our aim is to inventory colorectal cancer specialists' unmet decision support needs., Methods: We asked oncologists from the Dutch colorectal cancer group (DCCG), to participate in an online inventory questionnaire on their unmet decision support needs. To get more in-depth insight in required features of the DSS they need, we also conducted semi-structured telephone interviews., Results: Forty-one oncologists started the inventory questionnaire, and 27 of them completed all items. Of all respondents, 18 were surgeons (44%), 22 were medical oncologists (54%), and 28 (68%) had more than 10 years of experience treating mCRC. In both the inventory questionnaire and interviews, respondents expressed a need for an overarching DSS incorporating multiple treatment options, and presenting both the treatment benefits and harms. Respondents found it relevant for other outcomes, such as cost-effectiveness of treatment or quality of life, to be incorporated in DSS. There was also a wish for DSS incorporating an up-to-date "personalized" overview of the ongoing trials for which a specific patient is eligible., Conclusions: Experienced oncologists indicate that their treatment advice is currently almost solely based on the available clinical guidelines. They experience a lack of good quality DSS to help them personalize their treatment advice. New tools integrating multiple treatment options and providing a broad range of clinically relevant outcomes are urgently needed to stimulate and safeguard more personalized treatment decision-making.

Background: Decision-making regarding palliative treatment for patients with metastatic colorectal cancer (mCRC) is complex and comprises numerous decisions. Decision-making should be guided by the premise of maintaining and/or improving patients' quality of life, by patient preference, and by the trade-off between treatment benefits and harm. Decision support systems (DSSs) for clinicians (eg, nomograms) can assist in this process. The present systematic review aimed to provide a comprehensive overview of the available DSSs for incurable mCRC and to assess their clinical usefulness., Materials and Methods: A systematic literature search was performed in PubMed, Embase, and the Cochrane Library. We extracted information on the DSS characteristics and their discriminatory ability, calibration, and user-friendliness., Results: From 5205 studies, we identified 14 DSSs for decisions regarding palliative resection of the primary tumor (n = 3), radiotherapy for metastases (n = 2), treatment type (invasive vs. symptomatic only; n = 7), and selection of chemotherapy (n = 2). The predictors varied greatly among the DSSs, and only 1 DSS incorporated a genetic marker (ie, UGT1A1). None of the DSSs included > 1 treatment option, nor did any DSS present estimates of treatment benefits and harms. Five tools had not been externally validated, two had only been validated in < 35 patients, and the rest had only been validated in populations similar to the population used for their development. Discriminatory accuracy was generally moderate to poor. Calibration measures were only reported for 2 tools., Conclusion: A limited number of DSSs are available to support palliative treatment decisions for patients with mCRC, and the evidence regarding their discriminatory ability and calibration is too limited to recommend their use. New DSSs comparing multiple treatment options and presenting both treatment benefits and harms are needed., (Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.)

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.

Background: Individually tailored cancer treatment is essential to ensure optimal treatment and resource use. Treatments for incurable metastatic non-small cell lung cancer (NSCLC) are evolving rapidly, and decision support systems (DSS) for this patient population have been developed to balance benefits and harms for decision-making. The aim of this systematic review was to inventory DSS for stage IIIB/IV NSCLC patients., Methods: A systematic literature search was performed in Pubmed, Embase and the Cochrane Library. DSS were described extensively, including their predictors, model performances (i.e., discriminative ability and calibration), levels of validation and user friendliness., Results: The systematic search yielded 3531 articles. In total, 67 articles were included after additional reference tracking. The 39 identified DSS aim to predict overall survival and/or progression-free survival, but give no information about toxicity or cost-effectiveness. Various predictors were incorporated, such as performance status, serum and inflammatory markers, and patient and tumor characteristics. Some DSS were developed for the entire incurable NSCLC population, whereas others were specifically for patients with brain or spinal metastases. Few DSS had been validated externally using recent clinical data, and the discrimination and calibration were often poor., Conclusions: Many DSS have been developed for incurable NSCLC patients, but DSS are still lacking that are up-to-date with a good model performance, while covering the entire treatment spectrum. Future DSS should incorporate genetic and biological markers based on state-of-the-art evidence, and compare multiple treatment options to estimate survival, toxicity and cost-effectiveness.

Objectives: To assess the occurrence of questions that foster shared decision making, in particular cancer patients' understanding of treatment decisions and oncologists' understanding of patients' priorities, during consultations in which preference-sensitive decisions are discussed. Specifically, (a) regarding patient understanding, do oncologists ask about patients' preexisting knowledge, information preferences, and understanding and do patients and companions ask about the disease and treatment, and (b) regarding patient priorities, do oncologists ask about patients' treatment- and decision-related preferences and do patients and companions ask about the decision?, Methods: Audiotaped pretreatment consultations of 100 cancer patients with 32 oncologists about (neo)adjuvant treatment were coded and analyzed to document question type, topic, and initiative., Results: The oncologists ascertained prior knowledge in 50 patients, asked 24 patients about preferred (probability) information, and invited questions from 56 patients. The oncologists asked 32 patients about treatment preferences and/or for consent. Respectively, one-third and one-fifth of patients and companions asked about treatment benefits compared with three-quarters of them who asked about treatment harms and/or procedures., Conclusions: It would be helpful to patients if oncologists more often assessed patients' existing knowledge to tailor their information provision. Also, patients could receive treatment recommendations that better fit their personal situation if oncologists collected information on patients' views about treatments. Moreover, by educating patients to ask about treatment alternatives, benefits, and harms, patients may gain a better understanding of the choice they have., (Copyright © 2016 John Wiley & Sons, Ltd.)

Importance: Online prognostication tools such as PREDICT and Adjuvant! are increasingly used in clinical practice by oncologists to inform patients and guide treatment decisions about adjuvant systemic therapy. However, their validity for young breast cancer patients is debated., Objective: To assess first, the prognostic accuracy of PREDICT's and Adjuvant! 10-year all-cause mortality, and second, its breast cancer-specific mortality estimates, in a large cohort of breast cancer patients diagnosed <50 years., Design: Hospital-based cohort., Setting: General and cancer hospitals., Participants: A consecutive series of 2710 patients without a prior history of cancer, diagnosed between 1990 and 2000 with unilateral stage I-III breast cancer aged <50 years., Main Outcome Measures: Calibration and discriminatory accuracy, measured with C-statistics, of estimated 10-year all-cause and breast cancer-specific mortality., Results: Overall, PREDICT's calibration for all-cause mortality was good (predicted versus observed) mean difference : -1.1% (95%CI: -3.2%-0.9%; P = 0.28). PREDICT tended to underestimate all-cause mortality in good prognosis subgroups (range mean difference : -2.9% to -4.8%), overestimated all-cause mortality in poor prognosis subgroups (range mean difference : 2.6%-9.4%) and underestimated survival in patients < 35 by -6.6%. Overall, PREDICT overestimated breast cancer-specific mortality by 3.2% (95%CI: 0.8%-5.6%; P = 0.007); and also overestimated it seemingly indiscriminately in numerous subgroups (range mean difference : 3.2%-14.1%). Calibration was poor in the cohort of patients with the lowest and those with the highest mortality probabilities. Discriminatory accuracy was moderate-to-good for all-cause mortality in PREDICT (0.71 [95%CI: 0.68 to 0.73]), and the results were similar for breast cancer-specific mortality. Adjuvant!'s calibration and discriminatory accuracy for both all-cause and breast cancer-specific mortality were in line with PREDICT's findings., Conclusions: Although imprecise at the extremes, PREDICT's estimates of 10-year all-cause mortality seem reasonably sound for breast cancer patients <50 years; Adjuvant! findings were similar. Prognostication tools should be used with caution due to the intrinsic variability of their estimates, and because the threshold to discuss adjuvant systemic treatment is low. Thus, seemingly insignificant mortality overestimations or underestimations of a few percentages can significantly impact treatment decision-making., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

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.

Background: Shared decision making (SDM) is widely advocated, especially for preference-sensitive decisions like those on adjuvant treatment for early-stage cancer. Here, decision making involves a subjective trade-off between benefits and side-effects, and therefore, patients' informed preferences should be taken into account. If clinicians consciously or unconsciously steer patients towards the option they think is in their patients' best interest (i.e. implicit persuasion), they may be unwittingly subverting their own efforts to implement SDM. We assessed the frequency of use of implicit persuasion during consultations and whether the use of implicit persuasion was associated with expected treatment benefit and/or decision making., Methods: Observational study design in which consecutive consultations about adjuvant systemic therapy with stage I-II breast cancer patients treated at oncology outpatient clinics of general teaching hospitals and university medical centres were audiotaped, transcribed and coded by two researchers independently., Results: In total, 105 patients (median age = 59; range: 35-87 years) were included. A median of five (range: 2-10) implicitly persuasive behaviours were employed per consultation. The number of behaviours used did not differ by disease stage (P = 0.07), but did differ by treatment option presented (P = 0.002) and nodal status (P = 0.01). About 50% of patients with stage I or node-negative disease were steered towards undergoing chemotherapy, whereas 96% of patients were steered towards undergoing endocrine therapy, irrespective of expected treatment benefit. Decisions were less often postponed if more implicit persuasion was used (P = 0.03)., Interpretation: Oncologists frequently use implicit persuasion, steering patients towards the treatment option that they think is in their patients' best interest. Expected treatment benefit does not always seem to be the driving force behind implicit persuasion. Awareness of one's use of these steering behaviours during decision making is a first step to help overcome the performance gap between advocating and implementing SDM., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

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.

It is expected that rapid genetic counseling and testing (RGCT) will lead to increasing numbers of breast cancer (BC) patients knowing their BRCA1/2 carrier status before primary surgery. Considering the potential impact of knowing one's status on uptake and timing of risk-reducing contralateral mastectomy (RRCM), we aimed to evaluate trends over time in RRCM, and differences between carriers identified either before (predictively) or after (diagnostically) diagnosis. We collected data from female BRCA1/2 mutation carriers diagnosed with BC between 1995 and 2009 from four Dutch university hospitals. We compared the timing of genetic testing and RRCM in relation to diagnosis in 1995-2000 versus 2001-2009 for all patients, and predictively and diagnostically tested patients separately. Of 287 patients, 219 (76%) had a diagnostic BRCA1/2 test. In this cohort, the median time from diagnosis to DNA testing decreased from 28 months for those diagnosed between 1995 and 2000 to 14 months for those diagnosed between 2001 and 2009 (p < 0.001). Similarly, over time women in this cohort underwent RRCM sooner after diagnosis (median of 77 vs. 27 months, p = 0.05). Predictively tested women who subsequently developed BC underwent an immediate RRCM significantly more often than women who had a diagnostic test (21/61, 34%, vs. 13/170, 7.6 %, p < 0.001). Knowledge of carrying a BRCA1/2 mutation when diagnosed with BC influenced decisions concerning primary surgery. Additionally, in more recent years, women who had not undergone predictive testing were more likely to undergo diagnostic DNA testing and RRCM sooner after diagnosis. This suggests the need for RGCT to guide treatment decisions.

A large genotyping project within the Breast Cancer Association Consortium (BCAC) recently identified 41 associations between single nucleotide polymorphisms (SNPs) and overall breast cancer (BC) risk. We investigated whether the effects of these 41 SNPs, as well as six SNPs associated with estrogen receptor (ER) negative BC risk are modified by 13 environmental risk factors for BC. Data from 22 studies participating in BCAC were pooled, comprising up to 26,633 cases and 30,119 controls. Interactions between SNPs and environmental factors were evaluated using an empirical Bayes-type shrinkage estimator. Six SNPs showed interactions with associated p-values (pint ) <1.1 × 10(-3) . None of the observed interactions was significant after accounting for multiple testing. The Bayesian False Discovery Probability was used to rank the findings, which indicated three interactions as being noteworthy at 1% prior probability of interaction. SNP rs6828523 was associated with increased ER-negative BC risk in women ≥170 cm (OR = 1.22, p = 0.017), but inversely associated with ER-negative BC risk in women <160 cm (OR = 0.83, p = 0.039, pint = 1.9 × 10(-4) ). The inverse association between rs4808801 and overall BC risk was stronger for women who had had four or more pregnancies (OR = 0.85, p = 2.0 × 10(-4) ), and absent in women who had had just one (OR = 0.96, p = 0.19, pint = 6.1 × 10(-4) ). SNP rs11242675 was inversely associated with overall BC risk in never/former smokers (OR = 0.93, p = 2.8 × 10(-5) ), but no association was observed in current smokers (OR = 1.07, p = 0.14, pint = 3.4 × 10(-4) ). In conclusion, recently identified BC susceptibility loci are not strongly modified by established risk factors and the observed potential interactions require confirmation in independent studies., (© 2014 UICC.)

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.

Background: Adjuvant! Online is a prediction tool that can be used to aid clinical decision making in patients with breast cancer. It was developed in a patient population aged 69 years or younger, and subsequent validation studies included small numbers of older patients. Since older patients with breast cancer differ from younger patients in many aspects, the aim of this study was to investigate the validity of Adjuvant! Online in a large cohort of unselected older patients., Methods: We included patients from the population-based FOCUS cohort, which included all consecutive patients aged 65 years or older who were diagnosed with invasive or in-situ breast cancer between Jan 1, 1997, and Dec 31, 2004, in the southwestern part of the Netherlands. We included all patients who fulfilled the criteria as stated by Adjuvant! Online: patients with unilateral, unicentric, invasive adenocarcinoma; no evidence of metastatic or residual disease; no evidence of T4 features; and no evidence of inflammatory breast cancer. We entered data from all patients with the "average for age" comorbidity status (model 1) and with an individualised comorbidity status (model 2)., Findings: We included 2012 patients. Median age of patients in the cohort was 74·0 years (IQR 69·0-79·0). 904 (45%) of 2012 patients died during follow-up, whereas 326 (16%) patients had recurrence. Median follow-up for overall survival was 9·0 years (IQR 7·4-10·7), and 6·6 years (4·4-6·6) for patients without recurrence. Using model 1, Adjuvant! Online overestimated 10-year overall survival by 9·8% ([95% CI 5·9-13·7], p<0·0001) and 10-year cumulative recurrence survival by 8·7% ([6·7-10·7], p<0·0001). By contrast, when using model 2, Adjuvant! Online underestimated the 10-year overall survival by -17·1% ([95% CI -21·0 to -13·2], p<0·0001). However, when using model 2, Adjuvant! Online predicted cumulative recurrence accurately in all patients (-0·7% [95% CI -2·7-1·3], p=0·48)., Interpretation: Adjuvant! Online does not accurately predict overall survival and recurrence in older patients with early breast cancer., Funding: Dutch Cancer Foundation., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

The length of female reproductive lifespan is associated with multiple adverse outcomes, including breast cancer, cardiovascular disease and infertility. The biological processes that govern the timing of the beginning and end of reproductive life are not well understood. Genetic variants are known to contribute to ∼50% of the variation in both age at menarche and menopause, but to date the known genes explain <15% of the genetic component. We have used genome-wide association in a bivariate meta-analysis of both traits to identify genes involved in determining reproductive lifespan. We observed significant genetic correlation between the two traits using genome-wide complex trait analysis. However, we found no robust statistical evidence for individual variants with an effect on both traits. A novel association with age at menopause was detected for a variant rs1800932 in the mismatch repair gene MSH6 (P = 1.9 × 10(-9)), which was also associated with altered expression levels of MSH6 mRNA in multiple tissues. This study contributes to the growing evidence that DNA repair processes play a key role in ovarian ageing and could be an important therapeutic target for infertility.

Background: It is a challenge for oncologists to distinguish patients with breast cancer who can forego adjuvant systemic treatment without negatively affecting survival from those who cannot. Risk prediction models (RPMs) have been developed for this purpose. Oncologists seem to have embraced RPMs (particularly Adjuvant!) in clinical practice and often use them to communicate prognosis to patients. We performed a systematic review of published RPMs and provide an overview of the prognosticators incorporated and reported clinical validity. Subsequently, we selected the RPMs that are currently used in the clinic for a more in-depth assessment of clinical validity. Finally, we assessed lay comprehensibility of the reports generated by RPMs., Methods: Pubmed, EMBASE, and Web of Science were searched. Two reviewers independently selected relevant articles and extracted data. Agreement on article selection and data extraction was achieved in consensus meetings., Results: We identified RPMs based on clinical prognosticators (N = 6) and biomolecular features (N = 14). Generally predictions from RPMs seem to be accurate, except for patients ≤ 50 years or ≥ 75 years at diagnosis, in addition to Asian populations. RPM reports contain much medical jargon or technical details, which are seldom explained in lay terms., Conclusion: The accuracy of RPMs' prognostic estimates is suboptimal in some patient subgroups. This urgently needs to be addressed. In their current format, RPM reports are not conducive to patient comprehension. Communicating survival probabilities using RPM might seem straightforward, but it is fraught with difficulties. If not done properly, it can backfire and confuse patients. Evidence to guide best communication practice is needed.