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1.
Stat ; 13(1)2024.
Artigo em Inglês | MEDLINE | ID: mdl-39070170

RESUMO

Precision medicine is a framework for developing evidence-based medical recommendations that seeks to determine the optimal sequence of treatments tailored to all of the relevant patient-level characteristics which are observable. Because precision medicine relies on highly sensitive, patient-level data, ensuring the privacy of participants is of great importance. Dynamic treatment regimes (DTRs) provide one formalization of precision medicine in a longitudinal setting. Outcome-Weighted Learning (OWL) is a family of techniques for estimating optimal DTRs based on observational data. OWL techniques leverage support vector machine (SVM) classifiers in order to perform estimation. SVMs perform classification based on a set of influential points in the data known as support vectors. The classification rule produced by SVMs often requires direct access to the support vectors. Thus, releasing a treatment policy estimated with OWL requires the release of patient data for a subset of patients in the sample. As a result, the classification rules from SVMs constitute a severe privacy violation for those individuals whose data comprise the support vectors. This privacy violation is a major concern, particularly in light of the potentially highly sensitive medical data which are used in DTR estimation. Differential privacy has emerged as a mathematical framework for ensuring the privacy of individual-level data, with provable guarantees on the likelihood that individual characteristics can be determined by an adversary. We provide the first investigation of differential privacy in the context of DTRs and provide a differentially private OWL estimator, with theoretical results allowing us to quantify the cost of privacy in terms of the accuracy of the private estimators.

2.
EBioMedicine ; 105: 105221, 2024 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-38917512

RESUMO

BACKGROUND: Accurate prediction of the optimal dose for ß-lactam antibiotics in neonatal sepsis is challenging. We aimed to evaluate whether a reliable clinical decision support system (CDSS) based on machine learning (ML) can assist clinicians in making optimal dose selections. METHODS: Five ß-lactam antibiotics (amoxicillin, ceftazidime, cefotaxime, meropenem and latamoxef), commonly used to treat neonatal sepsis, were selected. The CDSS was constructed by incorporating the drug, patient, dosage, pharmacodynamic, and microbiological factors. The CatBoost ML algorithm was used to build the CDSS. Real-world studies were used to evaluate the CDSS performance. Virtual trials were used to compare the CDSS-optimized doses with guideline-recommended doses. FINDINGS: For a specific drug, by entering the patient characteristics and pharmacodynamic (PD) target (50%/70%/100% fraction of time that the free drug concentration is above the minimal inhibitory concentration [fT > MIC]), the CDSS can determine whether the planned dosing regimen will achieve the PD target and suggest an optimal dose. The prediction accuracy of all five drugs was >80.0% in the real-world validation. Compared with the PopPK model, the overall accuracy, precision, recall, and F1-Score improved by 10.7%, 22.1%, 64.2%, and 43.1%, respectively. Using the CDSS-optimized doses, the average probability of target concentration attainment increased by 58.2% compared to the guideline-recommended doses. INTERPRETATION: An ML-based CDSS was successfully constructed to assist clinicians in selecting optimal ß-lactam antibiotic doses. FUNDING: This work was supported by the National Natural Science Foundation of China; Distinguished Young and Middle-aged Scholar of Shandong University; National Key Research and Development Program of China.


Assuntos
Antibacterianos , Sistemas de Apoio a Decisões Clínicas , Aprendizado de Máquina , beta-Lactamas , Humanos , beta-Lactamas/administração & dosagem , beta-Lactamas/uso terapêutico , Recém-Nascido , Antibacterianos/uso terapêutico , Antibacterianos/administração & dosagem , Sepse Neonatal/tratamento farmacológico , Sepse Neonatal/diagnóstico , Testes de Sensibilidade Microbiana , Algoritmos
3.
Sci Rep ; 14(1): 5833, 2024 03 10.
Artigo em Inglês | MEDLINE | ID: mdl-38461349

RESUMO

Renal replacement therapy (RRT) is a crucial treatment for sepsis-associated acute kidney injury (S-AKI), but it is uncertain which S-AKI patients should receive immediate RRT. Identifying the characteristics of patients who may benefit the most from RRT is an important task. This retrospective study utilized a public database and enrolled S-AKI patients, who were divided into RRT and non-RRT groups. Uplift modeling was used to estimate the individual treatment effect (ITE) of RRT. The validity of different models was compared using a qini curve. After labeling the patients in the validation cohort, we characterized the patients who would benefit the most from RRT and created a nomogram. A total of 8289 patients were assessed, among whom 591 received RRT, and 7698 did not receive RRT. The RRT group had a higher severity of illness than the non-RRT group, with a Sequential Organ Failure Assessment (SOFA) score of 9 (IQR 6,11) vs. 5 (IQR 3,7). The 28-day mortality rate was higher in the RRT group than the non-RRT group (34.83% vs. 14.61%, p < 0.0001). Propensity score matching (PSM) was used to balance baseline characteristics, 458 RRT patients and an equal number of non-RRT patients were enrolled for further research. After PSM, 28-day mortality of RRT and non-RRT groups were 32.3% vs. 39.3%, P = 0.033. Using uplift modeling, we found that urine output, fluid input, mean blood pressure, body temperature, and lactate were the top 5 factors that had the most influence on RRT effect. The area under the uplift curve (AUUC) of the class transformation model was 0.068, the AUUC of SOFA was 0.018, and the AUUC of Kdigo-stage was 0.050. The class transformation model was more efficient in predicting individual treatment effect. A logistic regression model was developed, and a nomogram was drawn to predict whether an S-AKI patient can benefit from RRT. Six factors were taken into account (urine output, creatinine, lactate, white blood cell count, glucose, respiratory rate). Uplift modeling can better predict the ITE of RRT on S-AKI patients than conventional score systems such as Kdigo and SOFA. We also found that white blood cell count is related to the benefits of RRT, suggesting that changes in inflammation levels may be associated with the effects of RRT on S-AKI patients.


Assuntos
Injúria Renal Aguda , Sepse , Humanos , Estudos Retrospectivos , Prognóstico , Terapia de Substituição Renal/efeitos adversos , Injúria Renal Aguda/etiologia , Injúria Renal Aguda/terapia , Sepse/complicações , Sepse/terapia , Lactatos , Unidades de Terapia Intensiva
4.
BMC Health Serv Res ; 24(1): 341, 2024 Mar 14.
Artigo em Inglês | MEDLINE | ID: mdl-38486179

RESUMO

BACKGROUND: Telemedicine is often promoted as a possible solution to some of the challenges healthcare systems in many countries face, and an increasing number of studies evaluate the clinical effects. So far, the studies show varying results. Less attention has been paid to systemic factors, such as the context, implementation, and mechanisms of these interventions. METHODS: This study evaluates the experiences of patients and health personnel enrolled in a pragmatic randomized controlled trial comparing telemedicine-based follow-up of chronic conditions with usual care. Patients in the intervention group received an individual treatment plan together with computer tablets and home telemonitoring devices to report point-of-care measurements, e.g., blood pressure, blood glucose or oxygen saturation, and to respond to health related questions reported to a follow-up service. In response to abnormal measurement results, a follow-up service nurse would contact the patient and consider relevant actions. We conducted 49 interviews with patients and 77 interviews with health personnel and managers at the local centers. The interview data were analyzed using thematic analysis and based on recommendations for conducting process evaluation, considering three core aspects within the process of delivering a complex intervention: (1) context, (2) implementation, and (3) mechanisms of impact. RESULTS: Patients were mainly satisfied with the telemedicine-based service, and experienced increased safety and understanding of their symptoms and illness. Implementation of the service does, however, require dedicated resources over time. Slow adjustment of other healthcare providers may have contributed to the absence of reductions in the use of specialized healthcare and general practitioner (GP) services. An evident advantage of the service is its flexibility, yet this may also challenge cost-efficiency of the intervention. CONCLUSIONS: The implementation of a telemedicine-based service in primary healthcare is a complex process that is sensitive to contextual factors and that requires time and dedicated resources to ensure successful implementation. TRIAL REGISTRATION: The trial was registered in www. CLINICALTRIALS: gov (NCT04142710). Study start: 2019-02-09, Study completion: 2021-06-30, Study type: Interventional, Intervention/treatment: Telemedicine tablet and tools to perform measurements. Informed and documented consent was obtained from all subjects and next of kin participating in the study.


Assuntos
Clínicos Gerais , Telemedicina , Humanos , Glicemia , Atenção à Saúde
5.
Front Surg ; 11: 1277322, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38322409

RESUMO

Objective: To study the classification, diagnosis, and treatment strategies of complex tethered cord syndrome (C-TCS) on the basis of the patients' clinical symptoms, imaging findings, and therapeutic schedule. Methods: The clinical data of 126 patients with C-TCS admitted to our department from January 2015 to December 2020 were retrospectively analyzed. Classification criteria for C-TCS were established by analyzing the causes of C-TCS. Different surgical strategies were adopted for different types of C-TCS. The Kirollos grading, visual analogue scale (VAS), critical muscle strength, and Japanese Orthopaedic Association (JOA) scores were used to evaluate the surgical outcomes and explore individualized diagnosis and treatment strategies for C-TCS. Results: C-TCS was usually attributable to three or more types of tether-causing factors. The disease mechanisms could be categorized as pathological thickening and lipomatosis of the filum terminal (filum terminal type), arachnoid adhesion (arachnoid type), spina bifida with lipomyelomeningocele/meningocele (cele type), spinal lipoma (lipoma type), spinal deformity (bone type), and diastomyelia malformation (diastomyelia type). Patients with different subtypes showed complex and varied symptoms and required individualized treatment strategies. Conclusion: Since C-TCS is attributable to different tether-related factors, C-TCS classification can guide individualized surgical treatment strategies to ensure complete release of the tethered cord and reduce surgical complications.

6.
J Environ Manage ; 352: 119992, 2024 Feb 14.
Artigo em Inglês | MEDLINE | ID: mdl-38194870

RESUMO

This paper investigates the non-monetary motivations of farmers' adoption of agri-environmental policies. Unlike the monetary (income) motivations, non-monetary drivers can not be directly observed but can be identified from observational data within appropriate quasi-experimental designs. A theoretical justification of farmers' choices is first formulated and a consequent natural experiment setting is derived. The latter admits heterogeneous, i.e. Individual, Treatment Effects (ITE) that, in turn, can be interpreted in terms of more targeted and tailored policy expenditure. A Causal Forest (CF) approach is adopted to estimate these ITEs for both the treated and not treated units. The approach is applied to two balanced panel samples of Italian Farm Accountancy Data Network (FADN) farms observed over the 2008-2018 period and concerns agri-environmental policies delivered through the Common Agricultural Policy (CAP). Results show how heterogeneous the farmers' response and the associated non-monetary motivations can be, thus indicating room for a more efficient policy design.


Assuntos
Política Ambiental , Motivação , Agricultura/métodos , Fazendas , Fazendeiros , Florestas
7.
Soa Chongsonyon Chongsin Uihak ; 35(1): 22-28, 2024 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-38204737

RESUMO

Interventions for targeted symptoms are important when setting treatment strategies for individuals with autism spectrum disorder (ASD) and developmental disabilities. Especially, the goal should be to achieve individual "niche construction" by allowing them to select and adjust an environment where they can demonstrate their special characteristics and strengths. In addition, these choices should vary depending on the stage of development of each person with ASD and developmental disabilities. It is necessary to establish a detailed and systematic plan for diagnosis and treatment necessary for infants and toddlers, school placement in school age, and employment or self-reliance in adult transition period to establish customized treatment strategies that fit the individual level of people with ASD and developmental disabilities.

8.
J Trauma Dissociation ; 25(2): 248-278, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38146918

RESUMO

Dissociative Identity Disorder (DID) is a highly disabling diagnosis, characterized by the presence of two or more personality states which impacts global functioning, with a substantial risk of suicide. The International Society for the Study of Trauma and Dissociation (ISSTD) published guidelines for treating DID in 2011 that noted individual Psychodynamically Informed Psychotherapy (PDIP) was a cornerstone of treatment. This paper systematically reviews the evidence base for PDIP in the treatment of adults with DID according to the 2009 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Thirty-five articles were located and reviewed: seven prospective longitudinal publications, 13 case series and 15 case studies. Results suggested that PDIP has been widely deployed in DID to reported good effect with a range of treatment protocols and using multiple theoretical models. Despite the positive findings observed, the evidence base remains at the level of observational-descriptive design. Creative approaches in recent years have been developed, which add empirical weight to the use of PDIP as an effective treatment. The elevation to observational-analytic designs in the Evidence-Based Medicine hierarchy has yet to take place. Bearing in mind the challenges of research in PDIP, suggestions are offered for how the evidence base might develop.

9.
J Biopharm Stat ; : 1-18, 2023 Nov 13.
Artigo em Inglês | MEDLINE | ID: mdl-37955423

RESUMO

It is widely recognized that treatment effects could differ across subgroups of patients. Subgroup analysis, which assesses such heterogeneity, provides valuable information in developing personalized therapies. There has been extensive research developing novel statistical methods for subgroup identification. The recent contribution is a value-guided subgroup identification method that directly maximizes treatment benefit at the subgroup level for survival outcome, rather than relying on individual treatment effect estimation. In this paper, we first completed this framework by illustrating its application to continuous and binary outcomes. More importantly, we extended the original framework to account for the prognostic effects and named this new method Covariate-Adjusted Value-guided subgroup identification via boosting (CAVboost). The original method directly used the outcome to formulate the value function for subgroup identification. Since the outcome can further be decomposed as prognostic effects and treatment effects, specifying the prognostic effects as the covariates of a model for the outcome can single out the treatment effects and improve the power to detect them across subgroups. Our proposed CAVboost was based on this key idea. It used a covariate-adjusted treatment effect estimator, instead of the outcome itself, to formulate the value function for subgroup identification. CAVboost estimates the treatment effect by using covariates to account for the prognostic effects, which mimics the idea of using covariates in an ANCOVA estimator. We showed that CAVboost could effectively improve the subgroup identification capability for both continuous and binary outcomes.

10.
Artigo em Inglês | MEDLINE | ID: mdl-37922115

RESUMO

Psychotherapy has been proven to be effective on average, though patients respond very differently to treatment. Understanding which characteristics are associated with treatment effect heterogeneity can help to customize therapy to the individual patient. In this tutorial, we describe different meta-learners, which are flexible algorithms that can be used to estimate personalized treatment effects. More specifically, meta-learners decompose treatment effect estimation into multiple prediction tasks, each of which can be solved by any machine learning model. We begin by reviewing necessary assumptions for interpreting the estimated treatment effects as causal, and then give an overview over key concepts of machine learning. Throughout the article, we use an illustrative data example to show how the different meta-learners can be implemented in R. We also point out how current popular practices in psychotherapy research fit into the meta-learning framework. Finally, we show how heterogeneous treatment effects can be analyzed, and point out some challenges in the implementation of meta-learners.

11.
Eur J Heart Fail ; 25(11): 1962-1975, 2023 11.
Artigo em Inglês | MEDLINE | ID: mdl-37691140

RESUMO

AIMS: Although trials have proven the group-level effectiveness of various therapies for heart failure with reduced ejection fraction (HFrEF), important differences in absolute effectiveness exist between individuals. We developed and validated the LIFEtime-perspective for Heart Failure (LIFE-HF) model for the prediction of individual (lifetime) risk and treatment benefit in patients with HFrEF. METHODS AND RESULTS: Cox proportional hazards functions with age as the time scale were developed in the PARADIGM-HF and ATMOSPHERE trials (n = 15 415). Outcomes were cardiovascular death, heart failure (HF) hospitalization or cardiovascular death, and non-cardiovascular mortality. Predictors were age, sex, New York Heart Association class, prior HF hospitalization, diabetes mellitus, extracardiac vascular disease, systolic blood pressure, left ventricular ejection fraction, N-terminal pro-B-type natriuretic peptide, and glomerular filtration rate. The functions were combined in life-tables to predict individual overall and HF hospitalization-free survival. External validation was performed in the SwedeHF registry, ASIAN-HF registry, and DAPA-HF trial (n = 51 286). Calibration of 2- to 10-year risk was adequate, and c-statistics were 0.65-0.74. An interactive tool was developed combining the model with hazard ratios from trials to allow estimation of an individual's (lifetime) risk and treatment benefit in clinical practice. Applying the tool to the development cohort, combined treatment with a mineralocorticoid receptor antagonist, sodium-glucose cotransporter 2 inhibitor, and angiotensin receptor-neprilysin inhibitor was estimated to afford a median of 2.5 (interquartile range [IQR] 1.7-3.7) and 3.7 (IQR 2.4-5.5) additional years of overall and HF hospitalization-free survival, respectively. CONCLUSION: The LIFE-HF model enables estimation of lifelong overall and HF hospitalization-free survival, and (lifetime) treatment benefit for individual patients with HFrEF. It could serve as a tool to improve the management of HFrEF by facilitating personalized medicine and shared decision-making.


Assuntos
Insuficiência Cardíaca , Disfunção Ventricular Esquerda , Humanos , Insuficiência Cardíaca/tratamento farmacológico , Volume Sistólico/fisiologia , Função Ventricular Esquerda , Coração
13.
Int J Neural Syst ; 33(7): 2350036, 2023 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-37335255

RESUMO

Treatment effect estimation is of high-importance for both researchers and practitioners across many scientific and industrial domains. The abundance of observational data makes them increasingly used by researchers for the estimation of causal effects. However, these data suffer from several weaknesses, leading to inaccurate causal effect estimations, if not handled properly. Therefore, several machine learning techniques have been proposed, most of them focusing on leveraging the predictive power of neural network models to attain more precise estimation of causal effects. In this work, we propose a new methodology, named Nearest Neighboring Information for Causal Inference (NNCI), for integrating valuable nearest neighboring information on neural network-based models for estimating treatment effects. The proposed NNCI methodology is applied to some of the most well established neural network-based models for treatment effect estimation with the use of observational data. Numerical experiments and analysis provide empirical and statistical evidence that the integration of NNCI with state-of-the-art neural network models leads to considerably improved treatment effect estimations on a variety of well-known challenging benchmarks.


Assuntos
Aprendizado de Máquina , Redes Neurais de Computação , Causalidade
14.
Pharmaceutics ; 15(5)2023 May 22.
Artigo em Inglês | MEDLINE | ID: mdl-37242808

RESUMO

Mucopolysaccharidosis (MPS) is a group of rare metabolic diseases associated with reduced life expectancy and a substantial unmet medical need. Immunomodulatory drugs could be a relevant treatment approach for MPS patients, although they are not licensed for this population. Therefore, we aim to provide evidence justifying fast access to innovative individual treatment trials (ITTs) with immunomodulators and a high-quality evaluation of drug effects by implementing a risk-benefit model for MPS. The iterative methodology of our developed decision analysis framework (DAF) consists of the following steps: (i) a comprehensive literature analysis on promising treatment targets and immunomodulators for MPS; (ii) a quantitative risk-benefit assessment (RBA) of selected molecules; and (iii) allocation phenotypic profiles and a quantitative assessment. These steps allow for the personalized use of the model and are in accordance with expert and patient representatives. The following four promising immunomodulators were identified: adalimumab, abatacept, anakinra, and cladribine. An improvement in mobility is most likely with adalimumab, while anakinra might be the treatment of choice for patients with neurocognitive involvement. Nevertheless, a RBA should always be completed on an individual basis. Our evidence-based DAF model for ITTs directly addresses the substantial unmet medical need in MPS and characterizes a first approach toward precision medicine with immunomodulatory drugs.

15.
Pharmaceuticals (Basel) ; 16(3)2023 Mar 09.
Artigo em Inglês | MEDLINE | ID: mdl-36986515

RESUMO

Mucopolysaccharidoses (MPS) are a group of rare, heterogeneous, lysosomal storage disorders. Patients show a broad spectrum of clinical features with a substantial unmet medical need. Individual treatment trials (ITTs) might be a valid, time- and cost-efficient way to facilitate personalized medicine in the sense of drug repurposing in MPS. However, this treatment option has so far hardly been used-at least hardly been reported or published. Therefore, we aimed to investigate the awareness and utilization of ITTs among MPS clinicians, as well as the potential challenges and innovative approaches to overcome key hurdles, by using an international expert survey on ITTs, namely, ESITT. Although 74% (20/27) were familiar with the concept of ITTs, only 37% (10/27) ever used it, and subsequently only 15% (2/16) published their results. The indicated hurdles of ITTs in MPS were mainly the lack of time and know-how. An evidence-based tool, which provides resources and expertise needed for high-quality ITTs, was highly appreciated by the vast majority (89%; 23/26). The ESITT highlights a serious deficiency of ITT implementation in MPS-a promising option to improve its treatability. Furthermore, we discuss the challenges and innovative approaches to overcome key barriers to ITTs in MPS.

16.
Pharmaceutics ; 15(3)2023 Mar 10.
Artigo em Inglês | MEDLINE | ID: mdl-36986771

RESUMO

Probiotics have been used in human and veterinary medicine to increase resistance to pathogens and provide protection against external impacts for many years. Pathogens are often transmitted to humans through animal product consumption. Therefore, it is assumed that probiotics protecting animals may also protect the humans who consume them. Many tested strains of probiotic bacteria can be used for individualized therapy. The recently isolated Lactobacillus plantarum R2 Biocenol™ has proven to be preferential in aquaculture, and potential benefits in humans are expected. A simple oral dosage form should be developed to test this hypothesis by a suitable preparation method, i.e., lyophilization, allowing the bacteria to survive longer. Lyophilizates were formed from silicates (Neusilin® NS2N; US2), cellulose derivates (Avicel® PH-101), and saccharides (inulin; saccharose; modified starch® 1500). They were evaluated for their physicochemical properties (pH leachate, moisture content, water absorption, wetting time, DSC tests, densities, and flow properties); their bacterial viability was determined in conditions including relevant studies over 6 months at 4 °C and scanned under an electron microscope. Lyophilizate composed of Neusilin® NS2N and saccharose appeared to be the most advantageous in terms of viability without any significant decrease. Its physicochemical properties are also suitable for capsule encapsulation, subsequent clinical evaluation, and individualized therapy.

17.
Front Physiol ; 14: 1089637, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-36969605

RESUMO

The protection of physical activity (PA) against COVID-19 is a rising research interest. However, the role of physical activity intensity on this topic is yet unclear. To bridge the gap, we performed a Mendelian randomization (MR) study to verify the causal influence of light and moderate-to-vigorous PA on COVID-19 susceptibility, hospitalization, and severity. The Genome-Wide Association Study (GWAS) dataset of PA (n = 88,411) was obtained from the UK biobank and the datasets of COVID-19 susceptibility (n = 1,683,768), hospitalization (n = 1,887,658), and severity (n = 1,161,073) were extracted from the COVID-19 Host Genetics Initiative. A random-effect inverse variance weighted (IVW) model was carried out to estimate the potential causal effects. A Bonferroni correction was used for counteracting. The problem of multiple comparisons. MR-Egger test, MR-PRESSO test, Cochran's Q statistic, and Leave-One-Out (LOO) were used as sensitive analysis tools. Eventually, we found that light PA significantly reduced the risk of COVID-19 infection (OR = 0.644, 95% CI: 0.480-0.864, p = 0.003). Suggestive evidence indicated that light PA reduced the risks of COVID-19 hospitalization (OR = 0.446, 95% CI: 0.227 to 0.879, p = 0.020) and severe complications (OR = 0.406, 95% CI: 0.167-0.446, p = 0.046). By comparison, the effects of moderate-to-vigorous PA on the three COVID-19 outcomes were all non-significant. Generally, our findings may offer evidence for prescribing personalized prevention and treatment programs. Limited by the available datasets and the quality of evidence, further research is warranted to re-examine the effects of light PA on COVID-19 when new GWAS datasets emerge.

18.
Diagnostics (Basel) ; 13(3)2023 Jan 24.
Artigo em Inglês | MEDLINE | ID: mdl-36766529

RESUMO

A key step in providing management/treatment options to men with suspected prostate cancer (PCa) is categorizing the risk in terms of the presence of benign, low-risk, intermediate-risk, or high-risk disease. Our novel modality brings new evidence, based on the long-known hallmark characteristic of PCa-decreased zinc (Zn), which is the most direct metabolic sign of malignancy and its aggressiveness. To date, this approach has not been adopted for clinical use for a number of reasons that are described in this article, and which have been addressed by our approach. Zn has to be measured on fresh samples, prior to fixating in formalin; therefore, samples have to be scanned during the biopsy session. As Zn depletion occurs in the glands where the tumors develop, estimation of the glands' levels in the scanned tissue, along with their compactness, are essential for accurate diagnosis. Combined with the Zn depletion, this facilitates a reliable assessment of disease aggressiveness. Data gathered in the clinical study described here indicate that, in addition to improving the biopsy quality by real-time interactive guidance, a malignancy score can now be established for the entire prostate, allowing higher granularity personalized risk stratification and more decisive treatment decisions for all PCa patients.

19.
Proc Natl Acad Sci U S A ; 120(6): e2214889120, 2023 Feb 07.
Artigo em Inglês | MEDLINE | ID: mdl-36730196

RESUMO

We propose a model-free framework for sensitivity analysis of individual treatment effects (ITEs), building upon ideas from conformal inference. For any unit, our procedure reports the Γ-value, a number which quantifies the minimum strength of confounding needed to explain away the evidence for ITE. Our approach rests on the reliable predictive inference of counterfactuals and ITEs in situations where the training data are confounded. Under the marginal sensitivity model of [Z. Tan, J. Am. Stat. Assoc. 101, 1619-1637 (2006)], we characterize the shift between the distribution of the observations and that of the counterfactuals. We first develop a general method for predictive inference of test samples from a shifted distribution; we then leverage this to construct covariate-dependent prediction sets for counterfactuals. No matter the value of the shift, these prediction sets (resp. approximately) achieve marginal coverage if the propensity score is known exactly (resp. estimated). We describe a distinct procedure also attaining coverage, however, conditional on the training data. In the latter case, we prove a sharpness result showing that for certain classes of prediction problems, the prediction intervals cannot possibly be tightened. We verify the validity and performance of the methods via simulation studies and apply them to analyze real datasets.

20.
Health Policy ; 130: 104752, 2023 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-36812859

RESUMO

INTRODUCTION: Individual treatment attempts (ITAs) are a German concept for the treatment of individual patients by physicians with nonstandard therapeutic approaches. Due to the lack of evidence, ITAs come with a high amount of uncertainty regarding the risk-benefit ratio. Despite the high uncertainty, no prospective review and no systematic retrospective evaluation of ITAs are required in Germany. Our objective was to explore stakeholders' attitudes toward the retrospective evaluation (monitoring) or prospective evaluation (review) of ITAs. METHODS: We conducted a qualitative interview study among relevant stakeholder groups. We used the SWOT framework to represent the stakeholders' attitudes. We applied content analysis to the recorded and transcribed interviews in MAXQDA. RESULTS: Twenty interviewees participated and pointed to several arguments in favor of the retrospective evaluation of ITAs (e.g. knowledge gain about circumstances of ITAs). The interviewees expressed concerns regarding the validity and practical relevance of the evaluation results. The viewpoints on review addressed several contextual factors. CONCLUSION: The current situation with a complete lack of evaluation insufficiently reflects safety concerns. German health policy decision makers should be more explicit about where and why evaluation is needed. Prospective and retrospective evaluations should be piloted in areas of ITAs with a particularly high uncertainty.


Assuntos
Médicos , Humanos , Estudos Retrospectivos , Política de Saúde , Pesquisa Qualitativa , Alemanha
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