2022
DOI: 10.1200/op.21.00377
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Systemic Therapy Decision Making in Advanced Cancer: A Qualitative Analysis of Patient-Oncologist Encounters

Abstract: PURPOSE: We sought to characterize patient-oncologist communication and decision making about continuing or limiting systemic therapy in encounters after an initial consultation, with a particular focus on whether and how oncologists foster shared decision making (SDM). METHODS: We performed content analysis of outpatient oncology encounters at two US National Cancer Institute–designated cancer centers audio recorded between November 2010 and September 2014. A multidisciplinary team used a hybrid approach of i… Show more

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Cited by 7 publications
(5 citation statements)
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“…Of course, it is important to consider the potential for recall bias when generating data using retrospective interviews, rather than in real time, naturally occurring contexts using, for example ethnographic methods. Nonetheless given that recent studies have suggested that shared‐decision making does not always occur in the context of advanced cancer (Brom et al., 2017; Wasp et al., 2022), variation in the amount and type of information people desire (Lehmann et al., 2020) and uncertainties surrounding the potential benefits of immunotherapies (Tarbi & Pirl, 2022), further work in this area is clearly needed. Building on Hyatt et al.…”
Section: Discussionmentioning
confidence: 99%
“…Of course, it is important to consider the potential for recall bias when generating data using retrospective interviews, rather than in real time, naturally occurring contexts using, for example ethnographic methods. Nonetheless given that recent studies have suggested that shared‐decision making does not always occur in the context of advanced cancer (Brom et al., 2017; Wasp et al., 2022), variation in the amount and type of information people desire (Lehmann et al., 2020) and uncertainties surrounding the potential benefits of immunotherapies (Tarbi & Pirl, 2022), further work in this area is clearly needed. Building on Hyatt et al.…”
Section: Discussionmentioning
confidence: 99%
“…First, correlation does not imply causation and, therefore, cannot provide a basis for decision-making [13]. Second, understanding the causal relationships between ICM features and pCR after NST may lead to opportunities for targeted therapies and help oncologists and patients make informed decisions about continuing or limiting systemic therapy after initial consultation [14]. In a recent publication, Pearl et al [15] argued that counterfactual explanations could provide the highest level of interpretability in machine learning models and serve as a basis for generating causal inferences.…”
Section: Introductionmentioning
confidence: 99%
“…In the foregoing example, the correlation between alcohol consumption and increased risk of breast cancer may arise from confounding factors such as an indigent lifestyle, family history of breast cancer, or germline BRCA mutation, all of which have been shown to increase the likelihood of developing breast cancer [18]. Second, understanding the causal relationships between ICM features and pCR after NST may lead to opportunities for targeted therapies and help oncologists make informed decisions about continuing or limiting systemic therapy after initial consultation [19].…”
Section: Introductionmentioning
confidence: 99%
“…[3][4][5][6] Nevertheless, they are associated with important toxicity and impact on quality of life (QoL), which may be in conflict with patient values and preferences and, therefore, may be considered an indicator of poor-quality and aggressive care. [6][7][8][9][10] Recommendations for ADCs are usually based on their impact on survival outcomes, with less consideration of other critically important outcomes, such as QoL or quality of end of life (EoL) care. 3,4,11 Additionally, some guidelines recognize evidence gaps for particular clinical scenarios, such as second-line treatments for advanced biliary tract tumors.…”
Section: Introductionmentioning
confidence: 99%