Evaluating the Value of a New Prediction Model for Gastric Cancer

Berlin, Jesse A.; Catenacci, Daniel V.T.

doi:10.1001/jamanetworkopen.2021.37148

Cited by 2 publications

(1 citation statement)

References 3 publications

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“…Published: November 30, 2021November 30, . doi:10.1001November 30, /jamanetworkopen.2021 Open Access: This is an open access article distributed under the terms of the CC-BY License.…”

Section: Article Informationmentioning

confidence: 99%

Evaluating the Value of a New Prediction Model for Gastric Cancer

Berlin¹,

Catenacci²

2021

JAMA Netw Open

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The current publication by Chen and colleagues 1 presents a model aimed at predicting overall survival and disease-free survival in patients with gastric cancer. They argue that the current staging system, which uses routinely collected data, is limited in its ability to predict outcomes and, importantly, to predict potential benefits of chemotherapy. They focus on building a tumor-associated collagen signature (TACS) using data from the tumor microenvironment. Collagen is a major component of that tumor microenvironment, which can influence both cancer progression and response to chemotherapy.The authors used a sophisticated statistical modeling approach that allows consideration of large numbers of potential predictor variables, with limited overfitting of the models. (When models are overfit to a specific data set, they can be excellent for prediction in the current sample but not nearly as good at prediction in other populations.

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“…Published: November 30, 2021November 30, . doi:10.1001November 30, /jamanetworkopen.2021 Open Access: This is an open access article distributed under the terms of the CC-BY License.…”

Section: Article Informationmentioning

confidence: 99%

Evaluating the Value of a New Prediction Model for Gastric Cancer

Berlin¹,

Catenacci²

2021

JAMA Netw Open

Self Cite

View full text Add to dashboard Cite

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What Do Placebo and Nocebo Effects Have to Do With Health Equity? The Hidden Toll of Nocebo Effects on Racial and Ethnic Minority Patients in Clinical Care

et al. 2021

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A placebo effect is a positive clinical response to non-specific elements of treatment with a sham or inert replica of a drug, device, or surgical intervention. There is considerable evidence that placebo effects are driven by expectation of benefit from the intervention. Expectation is shaped by a patient’s past experience, observations of the experience of others, and written, verbal, or non-verbal information communicated during treatment. Not surprisingly, expectation in the clinical setting is strongly influenced by the attitude, affect, and communication style of the healthcare provider. While positive expectations can produce beneficial effects, negative information and experiences can lead to negative expectations, and consequently negative or nocebo effects. Key components identified and studied in the placebo and nocebo literature intersect with factors identified as barriers to quality care in the clinical setting for Black patients and other patients of color, including poor patient-clinician communication, medical mistrust, and perceived discrimination. Thus, in the context of discrimination and bias, the absence of placebo and presence of nocebo-generating influences in clinical settings could potentially reinforce racial and ethnic inequities in clinical outcomes and care. Healthcare inequities have consequences that ripple through the medical system, strengthening adverse short- and long-term outcomes. Here, we examine the potential for the presence of nocebo effects and absence of placebo effects to play a role in contributing to negative outcomes related to unequal treatment in the clinical encounter.

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Evaluating the Value of a New Prediction Model for Gastric Cancer

Cited by 2 publications

References 3 publications

Evaluating the Value of a New Prediction Model for Gastric Cancer

Evaluating the Value of a New Prediction Model for Gastric Cancer

What Do Placebo and Nocebo Effects Have to Do With Health Equity? The Hidden Toll of Nocebo Effects on Racial and Ethnic Minority Patients in Clinical Care

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