Machine Learning Analysis of Individual Tumor Lesions in Four Metastatic Colorectal Cancer Clinical Studies: Linking Tumor Heterogeneity to Overall Survival

Total tumor size (TS) metrics used in TS models in oncology do not consider tumor heterogeneity, which could help to better predict drug efficacy. We analyzed individual target lesions (iTLs) of patients with metastatic colorectal carcinoma (mCRC) to determine differences in TS dynamics by using the ClassIfication Clustering of Individual Lesions (CICIL) methodology. Results from subgroup analyses comparing genetic mutations and TS metrics were assessed and applied to survival analyses. Data from four mCRC clinical studies were analyzed (1781 patients, 6369 iTLs). CICIL was used to assess differences in lesion TS dynamics within a tissue (intra-class) or across different tissues (inter-class). First, lesions were automatically classified based on their location. Cross-correlation coefficients (CCs) determined if each pair of lesions followed similar or opposite dynamics. Finally, CCs were grouped by using the K-means clustering method. Heterogeneity in tumor dynamics was lower in the intra-class analysis than in the inter-class analysis for patients receiving cetuximab. More tumor heterogeneity was found in KRAS mutated patients compared to KRAS wild-type (KRASwt) patients and when using sum of longest diameters versus sum of products of diameters. Tumor heterogeneity quantified as the median patient’s CC was found to be a predictor of overall survival (OS) (HR = 1.44, 95% CI 1.08–1.92), especially in KRASwt patients. Intra- and inter-tumor tissue heterogeneities were assessed with CICIL. Derived metrics of heterogeneity were found to be a predictor of OS time. Considering differences between lesions’ TS dynamics could improve oncology models in favor of a better prediction of OS

Machine Learning Analysis of Individual Tumor Lesions in Four Metastatic Colorectal Cancer Clinical Studies: Linking Tumor Heterogeneity to Overall Survival

Total tumor size (TS) metrics used in TS models in oncology do not consider tumor heterogeneity, which could help to better predict drug efficacy. We analyzed individual target lesions (iTLs) of patients with metastatic colorectal carcinoma (mCRC) to determine differences in TS dynamics by using the ClassIfication Clustering of Individual Lesions (CICIL) methodology. Results from subgroup analyses comparing genetic mutations and TS metrics were assessed and applied to survival analyses. Data from four mCRC clinical studies were analyzed (1781 patients, 6369 iTLs). CICIL was used to assess differences in lesion TS dynamics within a tissue (intra-class) or across different tissues (inter-class). First, lesions were automatically classified based on their location. Cross-correlation coefficients (CCs) determined if each pair of lesions followed similar or opposite dynamics. Finally, CCs were grouped by using the K-means clustering method. Heterogeneity in tumor dynamics was lower in the intra-class analysis than in the inter-class analysis for patients receiving cetuximab. More tumor heterogeneity was found in KRAS mutated patients compared to KRAS wild-type (KRASwt) patients and when using sum of longest diameters versus sum of products of diameters. Tumor heterogeneity quantified as the median patient’s CC was found to be a predictor of overall survival (OS) (HR = 1.44, 95% CI 1.08–1.92), especially in KRASwt patients. Intra- and inter-tumor tissue heterogeneities were assessed with CICIL. Derived metrics of heterogeneity were found to be a predictor of OS time. Considering differences between lesions’ TS dynamics could improve oncology models in favor of a better prediction of OS

Drug Prescription and Delirium in Older Inpatients: Results From the Nationwide Multicenter Italian Delirium Day 2015-2016

Objective: This study aimed to evaluate the association between polypharmacy and delirium, the association of specific drug categories with delirium, and the differences in drug-delirium association between medical and surgical units and according to dementia diagnosis. Methods: Data were collected during 2 waves of Delirium Day, a multicenter delirium prevalence study including patients (aged 65 years or older) admitted to acute and long-term care wards in Italy (2015-2016); in this study, only patients enrolled in acute hospital wards were selected (n = 4,133). Delirium was assessed according to score on the 4 "A's" Test. Prescriptions were classified by main drug categories; polypharmacy was defined as a prescription of drugs from 5 or more classes. Results: Of 4,133 participants, 969 (23.4%) had delirium. The general prevalence of polypharmacy was higher in patients with delirium (67.6% vs 63.0%, P =.009) but varied according to clinical settings. After adjustment for confounders, polypharmacy was associated with delirium only in patients admitted to surgical units (OR = 2.9; 95% CI, 1.4-6.1). Insulin, antibiotics, antiepileptics, antipsychotics, and atypical antidepressants were associated with delirium, whereas statins and angiotensin receptor blockers exhibited an inverse association. A stronger association was seen between typical and atypical antipsychotics and delirium in subjects free from dementia compared to individuals with dementia (typical: OR = 4.31; 95% CI, 2.94-6.31 without dementia vs OR = 1.64; 95% CI, 1.19-2.26 with dementia; atypical: OR = 5.32; 95% CI, 3.44-8.22 without dementia vs OR = 1.74; 95% CI, 1.26-2.40 with dementia). The absence of antipsychotics among the prescribed drugs was inversely associated with delirium in the whole sample and in both of the hospital settings, but only in patients without dementia. Conclusions: Polypharmacy is significantly associated with delirium only in surgical units, raising the issue of the relevance of medication review in different clinical settings. Specific drug classes are associated with delirium depending on the clinical setting and dementia diagnosis, suggesting the need to further explore this relationship

Drug prescription and delirium in older inpatients: Results from the nationwide multicenter Italian Delirium Day 2015-2016

Objective: This study aimed to evaluate the association between polypharmacy and delirium, the association of specific drug categories with delirium, and the differences in drug-delirium association between medical and surgical units and according to dementia diagnosis. Methods: Data were collected during 2 waves of Delirium Day, a multicenter delirium prevalence study including patients (aged 65 years or older) admitted to acute and long-term care wards in Italy (2015-2016); in this study, only patients enrolled in acute hospital wards were selected (n = 4,133). Delirium was assessed according to score on the 4 "A's" Test. Prescriptions were classified by main drug categories; polypharmacy was defined as a prescription of drugs from 5 or more classes. Results: Of 4,133 participants, 969 (23.4%) had delirium. The general prevalence of polypharmacy was higher in patients with delirium (67.6% vs 63.0%, P =.009) but varied according to clinical settings. After adjustment for confounders, polypharmacy was associated with delirium only in patients admitted to surgical units (OR = 2.9; 95% CI, 1.4-6.1). Insulin, antibiotics, antiepileptics, antipsychotics, and atypical antidepressants were associated with delirium, whereas statins and angiotensin receptor blockers exhibited an inverse association. A stronger association was seen between typical and atypical antipsychotics and delirium in subjects free from dementia compared to individuals with dementia (typical: OR = 4.31; 95% CI, 2.94-6.31 without dementia vs OR = 1.64; 95% CI, 1.19-2.26 with dementia; atypical: OR = 5.32; 95% CI, 3.44-8.22 without dementia vs OR = 1.74; 95% CI, 1.26-2.40 with dementia). The absence of antipsychotics among the prescribed drugs was inversely associated with delirium in the whole sample and in both of the hospital settings, but only in patients without dementia. Conclusions: Polypharmacy is significantly associated with delirium only in surgical units, raising the issue of the relevance of medication review in different clinical settings. Specific drug classes are associated with delirium depending on the clinical setting and dementia diagnosis, suggesting the need to further explore this relationship

Understanding Factors Associated With Psychomotor Subtypes of Delirium in Older Inpatients With Dementia

Objectives: Few studies have analyzed factors associated with delirium subtypes. In this study, we investigate factors associated with subtypes of delirium only in patients with dementia to provide insights on the possible prevention and treatments. Design: This is a cross-sectional study nested in the \u201cDelirium Day\u201d study, a nationwide Italian point-prevalence study. Setting and Participants: Older patients admitted to 205 acute and 92 rehabilitation hospital wards. Measures: Delirium was evaluated with the 4-AT and the motor subtypes with the Delirium Motor Subtype Scale. Dementia was defined by the presence of a documented diagnosis in the medical records and/or prescription of acetylcholinesterase inhibitors or memantine prior to admission. Results: Of the 1057 patients with dementia, 35% had delirium, with 25.6% hyperactive, 33.1% hypoactive, 34.5% mixed, and 6.7% nonmotor subtype. There were higher odds of having venous catheters in the hypoactive (OR 1.82, 95% CI 1.18-2.81) and mixed type of delirium (OR 2.23, CI 1.43-3.46), whereas higher odds of urinary catheters in the hypoactive (OR 2.91, CI 1.92-4.39), hyperactive (OR 1.99, CI 1.23-3.21), and mixed types of delirium (OR 2.05, CI 1.36-3.07). We found higher odds of antipsychotics both in the hyperactive (OR 2.87, CI 1.81-4.54) and mixed subtype (OR 1.84, CI 1.24-2.75), whereas higher odds of antibiotics was present only in the mixed subtype (OR 1.91, CI 1.26-2.87). Conclusions and Implications: In patients with dementia, the mixed delirium subtype is the most prevalent followed by the hypoactive, hyperactive, and nonmotor subtype. Motor subtypes of delirium may be triggered by clinical factors, including the use of venous and urinary catheters, and the use of antipsychotics. Future studies are necessary to provide further insights on the possible pathophysiology of delirium in patients with dementia and to address the optimization of the management of potential risk factors