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.
New treatment options in cancer have resulted in increased use of health care resources near the end of life. We assessed health care use near the end of life of patients with advanced breast cancer (ABC). From the Southeast Netherlands Breast cancer (SONABRE) registry, we selected all deceased patients diagnosed with ABC in Maastricht University Medical Center between January 2007 and October 2017. Frequency of health care use in the last six months of life was described and predictors for health care use were assessed. Of 203 patients, 76% were admitted during the last six months, 6% to the intensive care unit (ICU) and 2% underwent cardiopulmonary resuscitation (CPR). Death in hospital occurred in 25%. Nine percent of patients received a new line of chemotherapy ≤30 days before death, which was associated with age <65 years and <1 year survival since diagnosis of metastases. In these patients, the hospital admission rate was 95%, of which 79% died in the hospital, mostly due to progressive disease (80%). In conclusion, the frequency of ICU-admission, CPR or a new line of chemotherapy ≤ 30 days before death was low. Most patients receiving a new line of chemotherapy ≤ 30 days before death, died in the hospital.
Caring for patients with incurable cancer presents unique challenges. Managing symptoms that evolve with changing clinical status and, at the same time, ensuring alignment with patient goals demands specific attention from clinicians. With care needs that often transcend traditional service provision boundaries, patients who seek palliation commonly interface with a team of providers that represents multiple disciplines across multiple settings. In this case study, we explore some of the dynamics of a cross-disciplinary approach to symptom management in an integrated outpatient radiotherapy service model. Providers who care for patients with incurable cancer must rely on one another to secure delivery of the right services at the right time by the right person. In a model of shared responsibilities, flexibility in who does what and when can enhance overall team performance. Adapting requires within-team and between-team monitoring of task and function execution for any given patient. This can be facilitated by a common understanding of the purpose of the clinical team and an awareness of the particular circumstances surrounding care provision. Backup behavior, in which one team member steps in to help another meet an expectation that would otherwise not be fulfilled, is a supportive team practice that may follow naturally in high-functioning teams. Such team processes as these have a place in the care of patients with incurable cancer and help to ensure that individual provider efforts more effectively translate into improved palliation for patients with unmet needs.
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: Although most low-risk ductal carcinoma in situ (DCIS) lesions will not progress to invasive breast cancer if left untreated, clinical guidelines advise surgery with/without radiotherapy for all women diagnosed with DCIS. There is therefore increasing concern about the possible overtreatment of DCIS. Currently, clinical trials are being conducted to investigate the safety of active surveillance in low-risk DCIS patients. It is hypothesized that, in future, both surgery and active surveillance will be accepted treatment strategies. Active surveillance is offered to women in the ongoing trials and is expected to become a standard DCIS management option in the future. Choosing whether to undergo surgery for DCIS or to opt for active surveillance can be a difficult decision fraught with uncertainty for both patients and oncologists. Good quality decision support tools such as prediction models and patient decision aids to guide decision making about DCIS management, including the option of active surveillance, are therefore urgently needed. The aim of this study is to identify and evaluate the quality of published decision aids and prediction models aiming to support decision making about DCIS treatment. Methods: A systematic literature review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement criteria. The databases Medline(ovid), Embase (ovid), Scopus, and TRIP were searched to identify published manuscripts describing the development and/or evaluation of DCIS decision aids and prediction models. The protocol was published in the PROSPERO database (ID CRD42020212297). The CHARMS (Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies) checklist was used to evaluate the methodological quality of prediction models and the IPDAS (International Patient Decision Aid Standards) checklist was used to evaluate the quality of decision aids. Data extraction was performed by two researchers with discrepancies resolved through consensus. Results: The review identified 10,636 publications, 33 describing the development and/or validation of four decision aids and seven clinical prediction models were selected (Table 1). The decision aids identified met at least 50% of the IPDAS quality criteria. However, most decision aids lacked tools to help patients reflect on the information received and to facilitate discussion of the information with their family and healthcare providers. Most prediction models were designed to predict the risk of a subsequent ipsilateral breast event after a primary DCIS. No models included the option of active surveillance. Sufficient, good quality, external validation was lacking for all prediction models identified. Conclusions: There are only a few decision aids available that can be used to support patients diagnosed with DCIS. These decision aids could be improved to facilitate the processing of information by patients and enhance communication between patients and their support system and healthcare providers. There is no prediction model that considers active surveillance as a management option for DCIS, and based on the available evidence, there is no prediction model that can be recommended for use in clinical practice. More and qualitatively better validations are required in the future. Table 1.Overview of DCIS decision aids and prediction models identifiedDCIS DECISION AIDSDecision aid by Berger-Hoger et al.(2014)Communication aid by De Morgan et al.(2009)onlineDeCISion.org by Ozanne et al.(2016)DCISoptions.org by COMET trial team(SABCS 2020)Target audience:Women with DCISCliniciansClinicians and women with DCISWomen with DCISLanguage:GermanEnglishEnglishEnglishEvaluation study conducted:YesYesNot reportedNot reportedDesign evaluation study:RCTInterviewNot applicableNot applicableSample size evaluation study:6425Not applicableNot applicableMain finding evaluation study:More active patient involvementCommunication tool assists shared decision makingNot applicableNot applicableImplementation study conducted:None retrievedNone retrievedNone retrievedNone retrieved% IPDAS criteria met regarding:Content87%57%65%78%Development process71%59%67%42%Effectiveness100%50%75%75%DCIS PREDICTION MODELSOncotype DCIS(Solin et al. (2013))DCISionRT/PreludeDX(Bremer et al. (2018))Van Nuysprognostic index(Silverstein et al. (1995))MSKCC DCIS nomogram(Rudlof et al. (2010))Patient prognostic score(Sagara et al. (2016))PredictCBC(Giardello et al. (2019))CBC Risk model(Chowdhury et al. (2017))Predicted outcome:Ipsilateral breast eventIpsilateral breast eventIpsilateral breast eventIpsilateral breast eventIpsilateral breast eventContralateral breast cancerContralateral breast cancerTool based on:Multigene assayBiomarkers + clinico-pathological factorsClinicopatho-logical factors onlyClinicopatho-logical factors onlyClinicopatho-logical factors onlyClinicopatho-logical factors onlyClinicopatho-logical factors onlyIntended to support decision making about:Need for adjuvant radiotherapyNeed for adjuvant radiotherapyType of surgery and need for radiotherapyNeed for adjuvant radiotherapyNeed for adjuvant radiotherapyScreening or prophylactic mastectomyScreening or prophylactic mastectomyRisk of bias based on CHARMS:ModerateModerateModerate/HighModerateLowLowLowNumber (external) validations:3193001Reported C-index/AUC0.68None reportedNone reported0.61-0.68None reported0.52None reportedThis work was supported by Cancer Research UK and by KWF Dutch Cancer Society (ref.C38317/A24043) Citation Format: Renée SJM Schmitz, Erica Wilthagen, Frederieke van Duijnhoven, Marja van Oirsouw, Ellen Verschuur, Thomas Lynch, Rinaa S Punglia, Shelley Hwang, Jelle Wesseling, Marjanka K Schmidt, Eveline Bleiker, Ellen G Engelhardt, Grand Challenge PRECISION consortium. Decision aids and risk prediction models to support decision making about DCIS treatment: A systematic literature review [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-22-04.
Background: Ductal carcinoma in situ (DCIS) is a potential precursor to breast cancer. Its incidence has increased multifold with the introduction of breast cancer screening and makes for 20% of all malignant breast lesions in women. DCIS has the potential to progress into invasive breast cancer. However, the majority of DCIS lesions are indolent and will never progress during the patient’s lifetime. Consequently, there is a growing concern of overdiagnosis and overtreatment for women with DCIS. The LORD trial is a non-randomized, patient preference trial comparing active surveillance to conventional treatment (i.e., breast conserving surgery with or without radiotherapy or mastectomy). The primary outcome of this trial is the percentage of women without an occurrence of ipsilateral invasive breast cancer after 10 years of follow up. Within the patient preference design, women are free to opt for either treatment arm. In addition to active surveillance of the DCIS, quality of life (QOL) of women included in the LORD trial is also actively monitored. The aims of this study were to: a) describe the distribution of participants within the treatment arms, b) identify women’s motives to opt for their preferred treatment arm, and c) assess factors associated with a preference for either treatment arm. Methods: Data from the baseline patient QOL questionnaire was collected. This questionnaire was completed after the women’s diagnosis and first consultation with their physician. Descriptive statistics were used to assess the distribution in both treatment arms. Thematic analyses were used to describe self-reported reasons for treatment selection derived from the open-ended question about treatment preference. Multivariable logistic regression analyses were used to assess associations between the patient characteristics and their preferred treatment arm. Results: In total 384 women completed the baseline questionnaire, of which 376 entered their final treatment decision. Of these women, 287 (76%) opted for active surveillance and 89 (24%) for conventional treatment. Most frequently cited reason for opting for active surveillance was that treatment was not yet necessary (55%). Also, patients’ reasons for preferring active surveillance alluded to a high level of trust in the active surveillance plan (24%) and that disease progression could be picked up and treated in a timely manner (14%). Furthermore, 11% of patients cited the advice of their healthcare professional as a reason for opting for active surveillance and 8% cited reasons relating to altruism. Most reported reasons for opting for the conventional treatment arm were avoiding unnecessary risks (26%), avoiding cancer worry (18%), the notion that what doesn’t belong, should be removed from the body (18%) and a need for closure (13%). In multivariable logistic regression analyses, high level of education (OR 2.17; 95%CI 1.09-4.38) and higher knowledge score (OR 1.8; 95%CI 1.07-3.02) were associated with a preference for conventional treatment. Furthermore, women opting for active surveillance more often reported the decision to be a shared decision between them and their healthcare professional (OR 2.30; 95%CI 1.18-4.47) compared to women who chose conventional treatment, who more often reported decision-making to be patient-driven. Age and tolerance of uncertainty were not significantly associated with treatment preference. Conclusion: The LORD trial is the first to actively offer women with low-risk DCIS a choice between conventional treatment and active surveillance. Within this trial, most women opt for active surveillance, even though clinical guidelines still recommend treatment for all women with DCIS. Women with low-risk DCIS report high levels of trust in their physicians and the safety of active surveillance. Their preferences also highlight the necessity to proof that de-escalating treatment of low-risk DCIS is safe. Citation Format: Renée S. Schmitz, Ellen G. Engelhardt, Miranda A. Gerritsma, Carine M. Sondermeijer, Sena Alaeikhanehshir, Ellen Verschuur, Marja van Oirsouw, Julia Houtzager, Rosalie Griffioen, Nina Bijker, Ritse M. Mann, Frederieke van Duijnhoven, Jelle Wesseling, Eveline Bleiker. Active surveillance versus conventional treatment in low-risk DCIS; women’s preferences in the LORD trial [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-05-11.
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