Individual Profiles Research Articles

Prediction of Hearing Help Seeking to Design a Recommendation Module of an mHealth Hearing App: Intensive Longitudinal Study of Feature Importance Assessment.

Mobile health (mHealth) solutions can improve the quality, accessibility, and equity of health services, fostering early rehabilitation. For individuals with hearing loss, mHealth apps might be designed to support the decision-making processes in auditory diagnostics and provide treatment recommendations to the user (eg, hearing aid need). For some individuals, such an mHealth app might be the first contact with a hearing diagnostic service and should motivate users with hearing loss to seek professional help in a targeted manner. However, personalizing treatment recommendations is only possible by knowing the individual's profile regarding the outcome of interest. This study aims to characterize individuals who are more or less prone to seeking professional help after the repeated use of an app-based hearing test. The goal was to derive relevant hearing-related traits and personality characteristics for personalized treatment recommendations for users of mHealth hearing solutions. In total, 185 (n=106, 57.3% female) nonaided older individuals (mean age 63.8, SD 6.6 y) with subjective hearing loss participated in a mobile study. We collected cross-sectional and longitudinal data on a comprehensive set of 83 hearing-related and psychological measures among those previously found to predict hearing help seeking. Readiness to seek help was assessed as the outcome variable at study end and after 2 months. Participants were classified into help seekers and nonseekers using several supervised machine learning algorithms (random forest, naïve Bayes, and support vector machine). The most relevant features for prediction were identified using feature importance analysis. The algorithms correctly predicted action to seek help at study end in 65.9% (122/185) to 70.3% (130/185) of cases, reaching 74.8% (98/131) classification accuracy at follow-up. Among the most important features for classification beyond hearing performance were the perceived consequences of hearing loss in daily life, attitude toward hearing aids, motivation to seek help, physical health, sensory sensitivity personality trait, neuroticism, and income. This study contributes to the identification of individual characteristics that predict help seeking in older individuals with self-reported hearing loss. Suggestions are made for their implementation in an individual-profiling algorithm and for deriving targeted recommendations in mHealth hearing apps.

Nutritional risk screening: a need to guide Alice in Nutritionland.

With the shifts in society, healthcare and the profile of the malnourished individual, a re-consideration of the goal of nutritional risk screening is needed: screening for malnutrition, or screening for risk of malnutrition? In this review article, we reflect on the role of nutritional risk screening in relation to prevention and treatment of malnutrition. Within the Global Leadership Initiative on Malnutrition (GLIM) Initiative, modified Delphi studies are currently being conducted to reach global consensus on the conceptual definition and operationalization of 'risk of malnutrition'. This is necessary because various studies have demonstrated that different nutritional screening tools identify different individuals, due to variability in screening tool criteria, which influences GLIM outcomes. Upon screening, three different situations can be distinguished: having risk factors for malnutrition without clear signs of presence of malnutrition, having mild signs of malnutrition (malnutrition in progress), or having obvious signs of malnutrition. The outcomes of the studies on 'risk of malnutrition' will guide the screening step within the GLIM process, and will help professionals to make informed choices regarding screening policy and screening tool(s).

Comparative Study of Sex Estimation by Mesiodistal width of Mandibular Canine and Mesiodistal width of Maxillary Canine in North Indian Population

Abbreviations: MD: Mesiodistal, SD: Standard deviation, mm: millimetres. Introduction: Various methods of identification such as anthropometry, stature estimation, dactylography, sex estimation, age estimation, DNA analysis, differentiation by blood groups and odontology are used in forensic medicine to create biological profile of an unknown individual. Estimation of sex is the first step towards identification of person. Determination of sex from skeletal remains is an essential task in medicolegal examination.Teeth are highly indestructible and reveal minimal turnover of natural substance hence teeth can be used for sex estimation. Mesiodistal parameter of mandibular and maxillary canine gave evidence of sex estimation due to sexual dimorphism. Aim: The aim of our study was to evaluate the sex estimation by mesiodistal width of mandibular canine and mesiodistal width of maxillary canine in north Indian population. Materials and Methods: The sample comprised of dental impression from 120 individuals (60 males and 60 females), all young adults between 20 and 35 years of age. Impressions of the teeth were made using irreversible hydrocolloid (alginate) material and casts poured in dental stone. Mesiodistal (MD) dimensions of mandibular and maxillary canine of both right and left side is measure by caliper. Results: Mean mandibular canine width of both right and left sidewere higher in male than female and were statistically significant whereas, mean maxillary canine width of both right and left side were slightly higher in male than female but were not statistically significant in young north Indian population. Left mandibular canine width (6%) was more sexually dimorphic than right mandibular canine width (5.1%). Whereas negligible sexual dimorphism shown by maxillary canine. Conclusion: The study confirmed that among maxillary and mandibular canine, mandibular canine can be used for sex estimation and shows significant sexual dimorphism.

Identification of dental sexual dimorphism in deciduous teeth: A cross sectional study

The study of sex diagnosis is essential to reconstruct the biological profile of an unknown individual. Two approaches are often used: morphometric and scopic. This three-dimensional morphometric study aimed to assess sexual dimorphism in temporary dentition.: A total of 200 dental impressions digitized in 3D using the Revopoint® POP2 3D scanner were used for this odontometric analysis. Discriminant statistical analysis (Student's t-test) revealed that boys had higher mean values than girls for all distances measured. A highly significant sexual dimorphism was observed in the temporary second molars. The distance between the mandibular canines was slightly greater in boys, although this difference was not statistically significant. In conclusion, odontometric parameters are a simple, reliable, and inexpensive method of sex determination. The temporary canines and second molars are the most dimorphic.

IgG Isotypes Targeting a Recombinant Chimeric Protein of Trypanosoma cruzi in Different Clinical Presentations of Chronic Chagas Disease.

Chagas disease (CD) is caused by the protozoan Trypanosoma cruzi, which leads to a spectrum of clinical presentations that range from asymptomatic to severe cardiac involvement. The host immune response plays a pivotal role in disease progression. Ig isotypes may contribute to disease pathogenesis. Investigating these components can provide insights into the immunopathogenic mechanisms underlying CD. This cross-sectional study aims to establish a correlation between the Ig profile of individuals infected with T. cruzi with the clinical forms of chronic CD. Serum samples were collected from partner institutions in different states of Brazil. Individuals diagnosed with chronic CD were categorized based on the clinical form of the disease. The indirect ELISA method using the recombinant chimeric Molecular Biology Institute of Paraná membrane protein 8.4 as the antigen was used to determine the Ig profile, including total IgG, IgG1, IgG2, IgG3, and IgG4. Ninety-seven serum samples from patients classified as negative (NEG, n = 38), indeterminate (IND, n = 24), mild cardiac (MC, n = 20), and severe cardiac (SC, n = 15) forms were analyzed. IgG1 exhibited greater levels compared with the other isotypes, showing a significant difference between the MC and IND groups. IgG3 levels were greater in individuals from the MC group compared with the SC group. IgG1 and IgG3 isotypes can serve as biomarkers to evaluate the progression of CD because they exhibit variations across clinical groups. Additional longitudinal studies are necessary to explore the relationship between antibody kinetics and the development of tissue damage.

Investigating implicit emotion processing in autism spectrum disorder across age groups: A cross-modal emotional priming study.

Cumulating evidence suggests that atypical emotion processing in autism may generalize across different stimulus domains. However, this evidence comes from studies examining explicit emotion recognition. It remains unclear whether domain-general atypicality also applies to implicit emotion processing in autism and its implication for real-world social communication. To investigate this, we employed a novel cross-modal emotional priming task to assess implicit emotion processing of spoken/sung words (primes) through their influence on subsequent emotional judgment of faces/face-like objects (targets). We assessed whether implicit emotional priming differed between 38 autistic and 38 neurotypical individuals across age groups as a function of prime and target type. Results indicated no overall group differences across age groups, prime types, and target types. However, differential, domain-specific developmental patterns emerged for the autism and neurotypical groups. For neurotypical individuals, speech but not song primed the emotional judgment of faces across ages. This speech-orienting tendency was not observed across ages in the autism group, as priming of speech on faces was not seen in autistic adults. These results outline the importance of the delicate weighting between speech- versus song-orientation in implicit emotion processing throughout development, providing more nuanced insights into the emotion processing profile of autistic individuals.

Effects of Calorie Restriction on Preserving Male Fertility Particularly in a State of Obesity.

Highlight the importance of exploring nutritional interventions that could be applied as alternative or supplementary therapeutic strategies to enhance men's fertility. Lifestyle choices haveprompted extensive discussions regarding its implications and applications as a complementary therapy. The growing concern over the decline in sperm quality underscores the urgency of investigating these alternative interventions. Calorie restriction (CR) has emerged as a promising strategy to improve male fertility. The efficacy of CR depends on factors like age, ethnicity and genetics. Clinical studies, such as CALERIE,have shown an improvement in serum testosterone level and sexual drive in men with or without obesity. Additionally, CR has been shown to positively impact sperm count and motility; however, its effects on sperm morphology and DNA fragmentation remain less clear, and the literature has shown discrepancies, mainly due to the nature of technically dependent assessment tools. The review advocates a personalized approach to CR, considering individual health profiles to maximize its benefits. It underscores the need for routine, accessible diagnostic techniques in male reproductive health. Itsuggests that future research should focus on personalized dietary interventions to improve male fertility and overall well-being in individuals with or without obesity and unravel CR's immediate and lasting effects on semen parameters in men without obesity.

Drug-Drug Interactions and Actual Harm to Hospitalized Patients: A Multicentre Study Examining the Prevalence Pre- and Post-Electronic Medication System Implementation.

Drug-drug interactions (DDIs) have potential to cause patient harm, including lowering therapeutic efficacy. This study aimed to (i) determine the prevalence of potential DDIs (pDDIs); clinically relevant DDIs (cDDIs), that is, DDIs that could lead to patient harm, taking into account a patient's individual clinical profile, drug effects and severity of potential harmful outcome; and subsequent actual harm among hospitalized patients and (ii) examine the impact of transitioning from paper-based medication charts to electronic medication management (eMM) on DDIs and patient harms. This was a secondary analysis of the control arm of a controlled pre-post study. Patients were randomly selected from three Australian hospitals. Retrospective chart review was conducted before and after the implementation of an eMM system, without accompanying clinical decision support alerts for DDIs. Harm was assessed by an expert panel. Of 1186 patient admissions, 70.1% (n = 831) experienced a pDDI, 42.6% (n = 505) a cDDI and 0.9% (n = 11) an actual harm in hospital. Of 15,860 pDDIs identified, 27.0% (n = 4285) were classified as cDDIs. The median number of pDDIs and cDDIs per 10 drugs were 6 [interquartile range (IQR) 2-13] and 0 (IQR 0-2), respectively. In cases where a cDDI was identified, both drugs were 44% less likely to be co-administered following eMM (adjusted odds ratio 0.56, 95% confidence interval 0.46-0.73). Although most patients experienced a pDDI during their hospital stay, less than one-third of pDDIs were clinically relevant. The low prevalence of harm identified raises questions about the value of incorporating DDI decision support into systems given the potential negative impacts of DDI alerts.

Prevention of recurrence of urolithiasis

Urolithiasis is one of the most frequent urological diseases. Identifying the causes of stone formation forms the basis for successful prevention of recurrence. Metabolic diagnostics and measures for prevention of recurrence are based on the assignment of the patient to alow-risk or high-risk group. Analysis of the urinary calculi is an essential prerequisite for identifying patients at risk. The general recommendations on diet and lifestyle are considered to be the basis of treatment. Depending on the type of stone and the individual biochemical risk profile of apatient, these general measures should be supplemented by targeted medical nutrition therapy and pharmacological treatment. Mixed stones can pose achallenge for the treatment and prevention of recurrence. Apersonalized treatment decision that takes the various components of mixed stones into account could further improve the prevention of recurrence of urolithiasis.

Predicting five-year interval second breast cancer risk in women with prior breast cancer.

Annual surveillance mammography is recommended for women with a personal history of breast cancer. Risk prediction models that estimate mammography failures such as interval second breast cancers could help to tailor surveillance imaging regimens to women's individual risk profiles. In a cohort of women with a history of breast cancer receiving surveillance mammography in the Breast Cancer Surveillance Consortium in 1996-2019, we used LASSO-penalized regression to estimate the probability of an interval second cancer (invasive cancer or ductal carcinoma in situ) in the one-year following a negative surveillance mammogram. Based on predicted risks from this one-year risk model, we generated cumulative risks of an interval second cancer for the five-year period following each mammogram. Model performance was evaluated using cross-validation in the overall cohort and within race and ethnicity strata. In 173,290 surveillance mammograms, we observed 496 interval cancers. One-year risk models were well-calibrated (expected/observed ratio = 1.00) with good accuracy (area under the receiver operating characteristic curve = 0.64). Model performance was similar across race and ethnicity groups. The median five-year cumulative risk was 1.20% (interquartile range 0.93-1.63%). Median five-year risks were highest in women who were under age 40 or pre- or peri-menopausal at diagnosis and those with estrogen receptor-negative primary breast cancers. Our risk model identified women at high risk of interval second breast cancers who may benefit from additional surveillance imaging modalities. Risk models should be evaluated to determine if risk-guided supplemental surveillance imaging improves early detection and decreases surveillance failures.

An Examination of Differences in Detected Versus Undetected Child-to-Parent Violence in Spanish Justice and Community Youth Samples

The number of crimes related to child-to-parent violence (CPV) has increased in recent years. Most cases are undetected. This is the first study to compare CPV-justice involved youth (CPV-JI/detected CPV) and CPV non-justice involved youth (CPV non-JI/undetected CPV), with the aim of examining differences in risk factors and pattern of violence. The sample included 306 Spanish youth (229 males, 77 females) aged 14 to 19 years: 83 CPV-JI, 105 CPV non-JI, and 115 non-CPV. The results show a worse individual, family, and social profile in CPV-JI youth compared with CPV non-JI youth, and in the latter compared with non-CPV youth. Undetected aggressors were more similar to detected aggressors than to non-aggressors. In addition, CPV-JI youth had higher scores in CPV-Q than CPV non-JI youth. The CPV-Q score that best classified detected versus undetected aggressors is 16 to 17 points, proving to be a useful instrument in classifying different types of CPV aggressors.

OLYMPUS-POPGEN: A synthetic population generation model to represent urban populations for assessing exposure to air quality.

With the new individual- and activity-based approaches to simulating exposure to air pollutants, exposure models must now provide synthetic populations that realistically reflect the demographic profiles of individuals in an urban territory. Demographic profiles condition the behavior of individuals in urban space (activities, mobility) and determine the resulting risks of exposure and environmental inequalities. In this context, there is a strong need to determine the relevance of the population modeling methods to reproduce the combinations of socio-demographic parameters in a population from the existing databases. The difficulty of accessing complete, high-resolution databases indeed proves to be very limiting for the ambitions of the different approaches. This work proposes to evaluate the potential of a statistical approach for the numerical modeling of synthetic populations, at the scale of dwellings and including the representation of coherent socio-demographic profiles. The approach is based on and validated against the existing open databases. The ambition is to be able to build upon such synthetic populations to produce a comprehensive assessment of the risk of environmental exposure that can be cross-referenced with lifestyles, indicators of social, professional or demographic category, and even health vulnerability data. The approach implemented here is based on the use of conditional probabilities to model the socio-demographic properties of individuals, via the deployment of a Monte Carlo Markov Chain (MCMC) simulation. Households are assigned to housing according to income and house price classes. The resulting population generation model was tested in the Paris region (Ile de France) for the year 2010, and applied to a population of almost 12 million individuals. The approach is based on the use of census and survey databases. Validation, carried out by comparison with regional census data, shows that the model accurately reproduces the demographic attributes of individuals (age, gender, professional category, income) as well as their combination, at both regional and sub-municipal levels. Notably, population distribution at the scale of the model buildings remains consistent with observed data patterns. The outcomes of this work demonstrate the ability of our approach to create, from public data, a coherent synthetic population with broad socio-demographic profiles. They give confidence for the use of this approach in an activity-based air quality exposure study, and thus for exploring the interrelations between social determinants and environmental risks. The non-specific nature of this work allows us to consider its extension to broader demographic profiles, including health indicators, and to different study regions.

Primary biliary cholangitis-response criteria of first-line treatment and perspectives of second-line therapy

Primary biliary cholangitis (PBC) is achronic cholestatic liver disease that can progress to liver cirrhosis if left untreated. Early diagnosis, initiation of therapy and, if necessary, adjustment of treatment are essential to prevent disease progression. The timing and thresholds for assessing adequate treatment response are inconsistently defined in the literature and can pose achallenge in clinical practice. In addition to providing aconcise overview of the guideline-based diagnostic work-up and first-line therapy, this study offers practical guidance for the evaluation of treatment response and options for second-line treatment in PBC. This article is based on the current European Association for the Study of the Liver (EASL) clinical practice guidelines for the management of PBC from 2017 as well as aliterature review of studies from 2017 to 2023, focusing on defining treatment response, assessing disease progression risk, and the approved and investigational agents for second-line therapy. There are varying definitions for asufficient response to ursodeoxycholic acid (UDCA). Therapeutic goals are tailored to the individual risk of disease progression. The lowest risk appears to be associated with normalization of alkaline phosphatase (AP) and serum bilirubin below 0.6 the upper limit of normal. Established second-line therapies include obeticholic acid and bezafibrate (off-label use), while other peroxisome proliferator-activated receptor (PPAR) agonists and combination therapies are under clinical investigation. Early evaluation of treatment response to UDCA is mandatory. In the case of insufficient treatment response, second-line therapy should be initiated according to the individual's risk profile.

Building Individual Player Performance Profiles According to Pre-Game Expectations and Goal Difference in Soccer.

Soccer player performance is influenced by multiple unpredictable factors. During a game, score changes and pre-game expectations affect the effort exerted by players. This study used GPS wearable sensors to track players' energy expenditure in 5-min intervals, alongside recording the goal timings and the win and lose probabilities from betting sites. A mathematical model was developed that considers pre-game expectations (e.g., favorite, non-favorite), endurance, and goal difference (GD) dynamics on player effort. Particle Swarm and Nelder-Mead optimization methods were used to construct these models, both consistently converging to similar cost function values. The model outperformed baselines relying solely on mean and median power per GD. This improvement is underscored by the mean absolute error (MAE) of 396.87±61.42 and root mean squared error (RMSE) of 520.69±88.66 achieved by our model, as opposed to the B1 MAE of 429.04±84.87 and RMSE of 581.34±185.84, and B2 MAE of 421.57±95.96 and RMSE of 613.47±300.11 observed across all players in the dataset. This research offers an enhancement to the current approaches for assessing players' responses to contextual factors, particularly GD. By utilizing wearable data and contextual factors, the proposed methods have the potential to improve decision-making and deepen the understanding of individual player characteristics.

Postpartum Oxytocin Treatment via the Mother Reprograms Long-Term Behavioral Disorders Induced by Early Life Stress on the Plasma and Brain Metabolome in the Rat.

The rat model of perinatal stress (PRS), in which exposure of pregnant dams to restraint stress reduces maternal behavior, is characterized by a metabolic profile that is reminiscent of the "metabolic syndrome". We aimed to identify plasma metabolomic signatures linked to long-term programming induced by PRS in aged male rats. This study was conducted in the plasma and frontal cortex. We also investigated the reversal effect of postpartum carbetocin (Cbt) on these signatures, along with its impact on deficits in cognitive, social, and exploratory behavior. We found that PRS induced long-lasting changes in biomarkers of secondary bile acid metabolism in the plasma and glutathione metabolism in the frontal cortex. Cbt treatment demonstrated disease-dependent effects by reversing the metabolite alterations. The metabolomic signatures of PRS were associated with long-term cognitive and emotional alterations alongside endocrinological disturbances. Our findings represent the first evidence of how early life stress may alter the metabolomic profile in aged individuals, thereby increasing vulnerability to CNS disorders. This raises the intriguing prospect that the pharmacological activation of oxytocin receptors soon after delivery through the mother may rectify these alterations.

Optimizing platelet inhibition in peripheral artery disease: A comparison of mono-antiplatelet therapy and dual-antiplatelet therapy using thromboelastography.

Antiplatelet therapy is used to prevent thrombosis in patients with peripheral artery disease (PAD) following revascularization. However, the current standard of care for these patients remains at the physician's discretion, varying from mono-antiplatelet therapy (MAPT) to dual-antiplatelet therapy (DAPT). Viscoelastic assays such as Thromboelastography with Platelet Mapping (TEG-PM) provide insight into individual coagulation profiles and measure real-time platelet function. This prospective, observational study looks at the differences in platelet function for patients on MAPT versus DAPT using TEG-PM. Patients with PAD undergoing revascularization were prospectively evaluated between December 2020 and June 2023. TEG-PM analysis compared platelet function for patients prescribed MAPT (aspirin or clopidogrel) at the initial encounter and DAPT (aspirin and clopidogrel) at the next visit. Platelet function measured in percent inhibition was evaluated at these visits, and within-group t-tests were performed. Of the 195 patients enrolled, 486 samples were analyzed by TEG-PM. Sixty-four patients met the study criteria. At the initial visit, 52 patients had been prescribed aspirin, and 12 patients had been prescribed clopidogrel. For patients initially prescribed aspirin MAPT, an increase of 96.8%in the mean ADP platelet inhibition was exhibited when transitioning to DAPT [22.0% vs. 43.3%, p < .01], as well as an increase of 34.6%in the mean AA platelet inhibition when transitioning to DAPT [60.9% vs. 82.0%, p < .01]. For patients prescribed initial clopidogrel MAPT, an increase of 100% in AA platelet inhibition was exhibited on DAPT compared to the MAPT state [42.3% vs. 84.6%, p < .01]. Patients on DAPT showed a significant increase in platelet inhibition when compared to initial aspirin MAPT. A significant difference in AA %platelet inhibition was shown for patients on DAPT when compared to initial clopidogrel MAPT. The results show that patients may benefit from DAPT post-revascularization. Personalizing antiplatelet therapy with objective viscoelastic testing to confirm adequate treatment may be the next step in optimizing patient outcomes to reduce thrombosis in PAD patients.

Immunotherapy and Radiation Therapy Combinatorial Approaches in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC), a prevalent and often fatal liver cancer, presents significant treatment challenges, especially in its advanced stages. This article delves into the promising approach of combining immunotherapy, particularly immune checkpoint inhibitors, with radiation therapy, a cornerstone of HCC management. Our review synthesizes current preclinical and clinical research, highlighting the potential synergistic effects of this combinational treatment. Emerging evidence suggests that this synergy enhances tumor control and improves patient survival rates. The combination leverages the localized, tumor-targeting ability of radiation therapy and the systemic, immune-boosting effects of immunotherapy, potentially overcoming the limitations inherent in each treatment modality when used separately. This integrative approach is especially promising in addressing the complex tumor microenvironment of HCC. However, the treatment landscape is nuanced, with challenges such as patient-specific response variability and potential resistance to therapies. Future research directions should focus on refining these combination strategies, tailoring them to individual patient profiles, and understanding the underlying mechanisms that govern the interaction between immunotherapy and radiation therapy. Such advancements could significantly improve HCC management, setting new standards for patient care and treatment efficacy.

Benefit finding in individuals undergoing maintenance hemodialysis in Shanghai: a latent profile analysis.

This multi-center cross-sectional study aimed to delineate latent profiles of benefit finding (BF) in individuals undergoing maintenance hemodialysis (MHD) in Shanghai and examine associations between these BF profiles, social support, and coping style. A total of 384 individuals undergoing MHD (mean age = 57.90, SD = 13.36) were assessed using the Benefit Finding Scale, Simplified Coping Style Questionnaire, and Perceived Social Support Scale. Latent profile analysis (LPA) identified distinct BF categories. Analysis of variance (ANOVA) evaluated the correlation between BF groups and demographic variables, while the relationship between BF, social support, and coping style was tested through correlation and multiple regression analyses. LPA identified three BF groups: rich BF (54.17%), moderate BF (41.14%), and poor BF (4.69%). Regression analyses indicated that positive coping and social support are protective factors for BF. Additionally, older age and heightened understanding of MHD correlated with higher BF levels. The findings highlighted the importance of recognizing different BF profiles in individuals on MHD and working toward promoting BF levels in the rich BF and moderate BF groups, while helping the poor BF group to identify and address their challenges. Medical professionals should consider interventions tailored to individual psychological profiles to improve mental health and quality of life outcomes in this population.

Recent Advances in Therapeutic Strategies to Improve Colorectal Cancer Treatment.

Colorectal cancer (CRC) is the second-leading cause of cancer-related mortality worldwide. CRC mortality results almost exclusively from metastatic disease (mCRC) for which systemic chemotherapy is often a preferred therapeutic option. Biomarker-based stratification of mCRC enables the use of precision therapy based on individual tumor mutational profiles. Activating mutations in the RAS/RAF/MAPK pathway downstream of EGFR signaling have, until recently, limited the use of EGFR-targeted therapies for mCRC; however, the development of anti-RAS and anti-RAF therapies together with improved strategies to limit compensatory signaling pathways is resulting in improved survival rates in several highly lethal mCRC sub-types (e.g., BRAF-mutant). The use of fluoropyrimidine (FP)-based chemotherapy regimens to treat mCRC continues to evolve contributing to improved long-term survival. Future advances in chemotherapy for mCRC will need to position development relative to the advances made in precision oncology.

Prediction of Effectiveness and Toxicities of Immune Checkpoint Inhibitors Using Real-World Patient Data.

Although immune checkpoint inhibitors (ICIs) have improved outcomes in certain patients with cancer, they can also cause life-threatening immunotoxicities. Predicting immunotoxicity risks alongside response could provide a personalized risk-benefit profile, inform therapeutic decision making, and improve clinical trial cohort selection. We aimed to build a machine learning (ML) framework using routine electronic health record (EHR) data to predict hepatitis, colitis, pneumonitis, and 1-year overall survival. Real-world EHR data of more than 2,200 patients treated with ICI through December 31, 2018, were used to develop predictive models. Using a prediction time point of ICI initiation, a 1-year prediction time window was applied to create binary labels for the four outcomes for each patient. Feature engineering involved aggregating laboratory measurements over appropriate time windows (60-365 days). Patients were randomly partitioned into training (80%) and test (20%) sets. Random forest classifiers were developed using a rigorous model development framework. The patient cohort had a median age of 63 years and was 61.8% male. Patients predominantly had melanoma (37.8%), lung cancer (27.3%), or genitourinary cancer (16.4%). They were treated with PD-1 (60.4%), PD-L1 (9.0%), and CTLA-4 (19.7%) ICIs. Our models demonstrate reasonably strong performance, with AUCs of 0.739, 0.729, 0.755, and 0.752 for the pneumonitis, hepatitis, colitis, and 1-year overall survival models, respectively. Each model relies on an outcome-specific feature set, though some features are shared among models. To our knowledge, this is the first ML solution that assesses individual ICI risk-benefit profiles based predominantly on routine structured EHR data. As such, use of our ML solution will not require additional data collection or documentation in the clinic.