Decision curve analysis as a framework to estimate the potential value of screening or other decision‐making aids

Martin, Michael S.; Wells, George A.; Crocker, Anne G.; Potter, Beth K.; Colman, Ian

doi:10.1002/mpr.1601

Cited by 4 publications

(8 citation statements)

References 48 publications

(67 reference statements)

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“…While others have observed that individuals of an ethnic or racial minority are more likely to have a complex pathway to mental health care, including the police or other parts of the justice system (which could result in a higher prevalence), [47][48][49] a lower prevalence of mental illness among minority inmates (13%) than white (25%) or Aboriginal (23%) inmates was previously reported. 30 We did not observe other hypothesized ethnic disparities. For example, similar treatment access by white and Indigenous inmates is inconsistent with findings indicating lower treatment rates by Indigenous persons in New Zealand prisons.…”

Section: Discussioncontrasting

confidence: 53%

Section: Discussionmentioning

confidence: 99%

“…Our prior work 30 found that screening in Canadian prisons performs at sensitivity (75%) and specificity (71%) that are comparable to the best-studied tools for use with prisoners. 15,31 However, while 79% of inmates with mental illness had contact with a mental health professional, only 46% received sustained treatment, 32 a figure that is comparable to access rates internationally.…”

mentioning

confidence: 87%

“…For example, newly admitted inmates at intake units (as opposed to regular prison wings) reported higher rates of preferring to care for themselves, unawareness of how to access services, and worries about how other inmates and staff would perceive them. 29 Our prior work 30 found that screening in Canadian prisons performs at sensitivity (75%) and specificity (71%) that are comparable to the best-studied tools for use with prisoners. 15,31 However, while 79% of inmates with mental illness had contact with a mental health professional, only 46% received sustained treatment, 32 a figure that is comparable to access rates internationally.…”

mentioning

confidence: 96%

“…15,31 However, while 79% of inmates with mental illness had contact with a mental health professional, only 46% received sustained treatment, 32 a figure that is comparable to access rates internationally. 8 –10 This may be caused in part by lower sensitivity of screening among those who did not self-report receiving treatment immediately prior to their incarceration and for racial minorities 30 ; sex, age, and regional differences were not considered. Barriers to care discussed previously may also explain why roughly one-third of those with clinical contact did not remain in treatment.…”

mentioning

confidence: 99%

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Mental Health Screening and Differences in Access to Care among Prisoners

et al. 2018

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Section: Discussioncontrasting

confidence: 53%

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 87%

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confidence: 96%

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confidence: 99%

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Mental Health Screening and Differences in Access to Care among Prisoners

et al. 2018

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Testing Approaches to Mental Health Screening at Prison Entry, Considering Both Concurrent and Predictive Validity in Men and Women

Dean,

Browne,

Chemjong

et al. 2024

International Journal of Forensic Mental Health

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Mental health screening at prison entry is important given the burden of unmet need and the challenge of prioritizing scarce resources, but the evidence to guide approaches to screening is limited. Screening at prison-entry (into prisons or jails receiving people at any stage of the trial or sentencing process) must achieve several aims, from uncovering untreated symptoms to recognizing the need to recommence treatment for established illness, and for a range of mental health conditions. The current exploratory observational study examines different approaches to screening and considers the results of both concurrent (structured diagnostic interview) and predictive (post-screening receipt of prison mental healthcare) methods for validation, in a sample ( n = 291) of men and women entering prison in New South Wales, Australia. A high prevalence of mental health problems, particularly for women was identified across the three screening approaches (i.e., screening for previous psychiatric history, current symptoms, and psychological distress). No single screening approach was superior across validation methods, supporting a broad approach to mental health screening, and differences in validity outcomes were seen between men and women. Prioritizing sensitivity to avoid false-negative cases requires a broad approach to prison-entry mental health screening but a second-stage triage assessment is likely necessary.

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Two machine learning-based nomogram to predict risk and prognostic factors for liver metastasis from pancreatic neuroendocrine tumors: a multicenter study

Li¹,

Huang²,

Liao³

et al. 2023

BMC Cancer

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Background Pancreatic neuroendocrine tumors (PNETs) are one of the most common endocrine tumors, and liver metastasis (LMs) are the most common location of metastasis from PNETS; However, there is no valid nomogram to predict the diagnosis and prognosis of liver metastasis (LMs) from PNETs. Therefore, we aimed to develop a valid predictive model to aid physicians in making better clinical decisions. Methods We screened patients in the Surveillance, Epidemiology, and End Results (SEER) database from 2010–2016. Feature selection was performed by machine learning algorithms and then models were constructed. Two nomograms were constructed based on the feature selection algorithm to predict the prognosis and risk of LMs from PNETs. We then used the area under the curve (AUC), receiver operating characteristic (ROC) curve, calibration plot and consistency index (C-index) to evaluate the discrimination and accuracy of the nomograms. Kaplan-Meier (K-M) survival curves and decision curve analysis (DCA) were also used further to validate the clinical efficacy of the nomograms. In the external validation set, the same validation is performed. Results Of the 1998 patients screened from the SEER database with a pathological diagnosis of PNET, 343 (17.2%) had LMs at the time of diagnosis. The independent risk factors for the occurrence of LMs in PNET patients included histological grade, N stage, surgery, chemotherapy, tumor size and bone metastasis. According to Cox regression analysis, we found that histological subtype, histological grade, surgery, age, and brain metastasis were independent prognostic factors for PNET patients with LMs. Based on these factors, the two nomograms demonstrated good performance in model evaluation. Conclusion We developed two clinically significant predictive models to aid physicians in personalized clinical decision-makings.

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Decision curve analysis as a framework to estimate the potential value of screening or other decision‐making aids

Abstract: Although screening has potential to increase detection of treatment, important subgroup differences exist. Greater consideration of responses to positive screens or alternatives to screening are needed to maximize the impact of efforts to improve detection and treatment of mental illness.

Cited by 4 publications

References 48 publications

Mental Health Screening and Differences in Access to Care among Prisoners

Mental Health Screening and Differences in Access to Care among Prisoners

Testing Approaches to Mental Health Screening at Prison Entry, Considering Both Concurrent and Predictive Validity in Men and Women

Two machine learning-based nomogram to predict risk and prognostic factors for liver metastasis from pancreatic neuroendocrine tumors: a multicenter study

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