Nevin Manimala

Pharm Stat. 2025 Sep-Oct;24(5):e70033. doi: 10.1002/pst.70033.

ABSTRACT

For toxicology studies, the validation of the concurrent control group by historical control data (HCD) has become requirements. This validation is usually done by historical control limits (HCL), which should cover the observations of the concurrent control with a predefined level of confidence. In many applications, HCL are applied to dichotomous data, for example, the number of rats with a tumor versus the number of rats without a tumor (carcinogenicity studies) or the number of cells with a micronucleus out of a total number of cells. Dichotomous HCD may be overdispersed and can be heavily right- (or left-) skewed, which is usually not taken into account in the practical applications of HCL. To overcome this problem, four different prediction intervals (two frequentist, two Bayesian), that can be applied to such data, are proposed. Based on comprehensive Monte-Carlo simulations, the coverage probabilities of the proposed prediction intervals were compared to heuristical HCL typically used in daily toxicological routine (historical range, limits of the np-chart, mean ± $$ pm $$ 2 SD). Our simulations reveal, that frequentist bootstrap calibrated prediction intervals control the type-1-error best, but, also prediction intervals calculated based on Bayesian generalized linear mixed models appear to be practically applicable. Contrary, all heuristics fail to control the type-1-error. The application of HCL is demonstrated based on a real life data set containing historical controls from long-term carcinogenicity studies run on behalf of the U.S. National Toxicology Program. The proposed frequentist prediction intervals are publicly available from the R package predint, whereas R code for the computation of the two Bayesian prediction intervals is provided via GitHub.

PMID:40947486 | DOI:10.1002/pst.70033

Pharm Stat. 2025 Sep-Oct;24(5):e70033. doi: 10.1002/pst.70033.

ABSTRACT

For toxicology studies, the validation of the concurrent control group by historical control data (HCD) has become requirements. This validation is usually done by historical control limits (HCL), which should cover the observations of the concurrent control with a predefined level of confidence. In many applications, HCL are applied to dichotomous data, for example, the number of rats with a tumor versus the number of rats without a tumor (carcinogenicity studies) or the number of cells with a micronucleus out of a total number of cells. Dichotomous HCD may be overdispersed and can be heavily right- (or left-) skewed, which is usually not taken into account in the practical applications of HCL. To overcome this problem, four different prediction intervals (two frequentist, two Bayesian), that can be applied to such data, are proposed. Based on comprehensive Monte-Carlo simulations, the coverage probabilities of the proposed prediction intervals were compared to heuristical HCL typically used in daily toxicological routine (historical range, limits of the np-chart, mean ± $$ pm $$ 2 SD). Our simulations reveal, that frequentist bootstrap calibrated prediction intervals control the type-1-error best, but, also prediction intervals calculated based on Bayesian generalized linear mixed models appear to be practically applicable. Contrary, all heuristics fail to control the type-1-error. The application of HCL is demonstrated based on a real life data set containing historical controls from long-term carcinogenicity studies run on behalf of the U.S. National Toxicology Program. The proposed frequentist prediction intervals are publicly available from the R package predint, whereas R code for the computation of the two Bayesian prediction intervals is provided via GitHub.

PMID:40947486 | DOI:10.1002/pst.70033

Eur J Med Res. 2025 Sep 15;30(1):845. doi: 10.1186/s40001-025-03170-6.

ABSTRACT

BACKGROUND: The lactate-to-albumin ratio (LAR) has emerged as a composite biomarker reflecting metabolic stress and nutritional status. This study aimed to evaluate the association between the LAR and 28 day mortality in hypertensive patients with atrial fibrillation (AF).

METHODS: We conducted a retrospective cohort study using the MIMIC-IV v3.1 database. Patients were screened for inclusion based on predefined criteria, resulting in a final cohort of 1087 eligible patients. Mortality within 28 days of ICU admission was the primary endpoint. Statistical analyses included LASSO regression and multivariate Cox regression, receiver operating characteristic (ROC) curve, and Kaplan‒Meier survival curve analyses.

RESULTS: The overall 28 day mortality rate was 22.8% (n = 248). Compared with survivors, nonsurvivors presented significantly higher LAR values (0.74 vs. 0.52, p < 0.001). Multivariate analyses indicated that the LAR was an independent predictor of 28-day mortality (HR 1.03, 95% CI 1.01-1.06, p < 0.05), even after adjusting for multiple clinical confounders. ROC analysis confirmed that the LAR had superior predictive ability (AUC 0.661) compared with other biomarkers. Kaplan‒Meier survival analysis revealed significant differences in mortality between the high- and low-LAR groups (HR 2.55, 95% CI 1.97-3.30, p < 0.05).

CONCLUSIONS: The LAR is an independent predictor of short-term mortality in hypertensive patients with AF. As a practical and easily applicable biomarker, the LAR holds significant potential for early risk stratification and tailored management in this high-risk population. Our findings underscore the importance of integrating LAR into clinical practice to optimize patient outcomes in critical care settings.

PMID:40947484 | DOI:10.1186/s40001-025-03170-6

Eur J Med Res. 2025 Sep 15;30(1):845. doi: 10.1186/s40001-025-03170-6.

ABSTRACT

BACKGROUND: The lactate-to-albumin ratio (LAR) has emerged as a composite biomarker reflecting metabolic stress and nutritional status. This study aimed to evaluate the association between the LAR and 28 day mortality in hypertensive patients with atrial fibrillation (AF).

METHODS: We conducted a retrospective cohort study using the MIMIC-IV v3.1 database. Patients were screened for inclusion based on predefined criteria, resulting in a final cohort of 1087 eligible patients. Mortality within 28 days of ICU admission was the primary endpoint. Statistical analyses included LASSO regression and multivariate Cox regression, receiver operating characteristic (ROC) curve, and Kaplan‒Meier survival curve analyses.

RESULTS: The overall 28 day mortality rate was 22.8% (n = 248). Compared with survivors, nonsurvivors presented significantly higher LAR values (0.74 vs. 0.52, p < 0.001). Multivariate analyses indicated that the LAR was an independent predictor of 28-day mortality (HR 1.03, 95% CI 1.01-1.06, p < 0.05), even after adjusting for multiple clinical confounders. ROC analysis confirmed that the LAR had superior predictive ability (AUC 0.661) compared with other biomarkers. Kaplan‒Meier survival analysis revealed significant differences in mortality between the high- and low-LAR groups (HR 2.55, 95% CI 1.97-3.30, p < 0.05).

CONCLUSIONS: The LAR is an independent predictor of short-term mortality in hypertensive patients with AF. As a practical and easily applicable biomarker, the LAR holds significant potential for early risk stratification and tailored management in this high-risk population. Our findings underscore the importance of integrating LAR into clinical practice to optimize patient outcomes in critical care settings.

PMID:40947484 | DOI:10.1186/s40001-025-03170-6

Int Urol Nephrol. 2025 Sep 14. doi: 10.1007/s11255-025-04780-z. Online ahead of print.

ABSTRACT

OBJECTIVE: The aim is to investigate the correlation between renal maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), molecular kidney volume (MKV), and total kidney uptake (TKU), which are indicators of the PSMA kidney uptake pattern in ⁶⁸Ga-PSMA-11 PET/CT imaging and kidney function tests. We secondarily aim to investigate how accurately renal parameters obtained from ⁶⁸Ga-PSMA-11 PET/CT can provide information about the patient’s kidney functions.

METHODS: The study included 196 patients with prostate cancer who underwent ⁶⁸Ga-PSMA-11 PET/CT imaging for staging purposes. Semiquantitative analyses were performed on the kidneys in the PET/CT images, and renal SUVmax, SUVmean, MKV, TKU values, as well as anatomical kidney volume (CT-KV) from CT imaging, were calculated. The patients’ concurrent laboratory results, including eGFR, BUN, and creatinine levels, were recorded. Statistical analyses were performed using the SPSS 22 software. The Spearman test was used to determine the correlation between the parameters. The ANOVA test was used for intergroup comparisons, and the Tamhane test was used for post-hoc analyses.

RESULTS: When comparing eGFR, BUN, and creatinine values with PET/CT renal parameters, a significant correlation was found between eGFR and MKV (r = 0.397), TKU (r = 0.271), and CT-KV (r = 0.216). Similar correlations were also observed for BUN and creatinine. When patients were grouped based on eGFR values, Group 1 (eGFR > 90; normal) included 75 patients, Group 2 (eGFR: 89-60; mild reduction) included 98 patients, and Group 3 (eGFR: 59-30; moderate reduction) included 21 patients. Significant differences were observed between the groups in terms of TKU, MKV, and CT-KV. In post-hoc analyses, the most significant parameter was MKV.

CONCLUSION: ⁶⁸Ga-PSMA-11 PET/CT-derived renal parameters, particularly the molecular kidney volume (MKV), exhibit a significant positive correlation with renal function and demonstrate a significant decrease in patients with renal dysfunction compared to those with normal renal function.

PMID:40947457 | DOI:10.1007/s11255-025-04780-z

Int Urol Nephrol. 2025 Sep 14. doi: 10.1007/s11255-025-04780-z. Online ahead of print.

ABSTRACT

OBJECTIVE: The aim is to investigate the correlation between renal maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), molecular kidney volume (MKV), and total kidney uptake (TKU), which are indicators of the PSMA kidney uptake pattern in ⁶⁸Ga-PSMA-11 PET/CT imaging and kidney function tests. We secondarily aim to investigate how accurately renal parameters obtained from ⁶⁸Ga-PSMA-11 PET/CT can provide information about the patient’s kidney functions.

METHODS: The study included 196 patients with prostate cancer who underwent ⁶⁸Ga-PSMA-11 PET/CT imaging for staging purposes. Semiquantitative analyses were performed on the kidneys in the PET/CT images, and renal SUVmax, SUVmean, MKV, TKU values, as well as anatomical kidney volume (CT-KV) from CT imaging, were calculated. The patients’ concurrent laboratory results, including eGFR, BUN, and creatinine levels, were recorded. Statistical analyses were performed using the SPSS 22 software. The Spearman test was used to determine the correlation between the parameters. The ANOVA test was used for intergroup comparisons, and the Tamhane test was used for post-hoc analyses.

RESULTS: When comparing eGFR, BUN, and creatinine values with PET/CT renal parameters, a significant correlation was found between eGFR and MKV (r = 0.397), TKU (r = 0.271), and CT-KV (r = 0.216). Similar correlations were also observed for BUN and creatinine. When patients were grouped based on eGFR values, Group 1 (eGFR > 90; normal) included 75 patients, Group 2 (eGFR: 89-60; mild reduction) included 98 patients, and Group 3 (eGFR: 59-30; moderate reduction) included 21 patients. Significant differences were observed between the groups in terms of TKU, MKV, and CT-KV. In post-hoc analyses, the most significant parameter was MKV.

CONCLUSION: ⁶⁸Ga-PSMA-11 PET/CT-derived renal parameters, particularly the molecular kidney volume (MKV), exhibit a significant positive correlation with renal function and demonstrate a significant decrease in patients with renal dysfunction compared to those with normal renal function.

PMID:40947457 | DOI:10.1007/s11255-025-04780-z

Clin Oral Investig. 2025 Sep 15;29(10):450. doi: 10.1007/s00784-025-06546-4.

ABSTRACT

OBJECTIVE: This study aimed to analyze accident-related traumatic dental injury (TDI) data to determine the occurrence, characteristics, and types of dental injuries in primary and permanent dentitions of underage patients attending a university clinic.

MATERIALS AND METHODS: A retrospective observational study was conducted at the Clinic of Orthodontics and Pediatric Dentistry of Zurich from 2010 to 2019 and involved children with accident-related TDIs from the ages of 0 to 18 years old. Data regarding patient- and trauma-related characteristics were extracted and analyzed statistically according to dentition, tooth, age, sex, and time elapsed before visiting the dentist at 5%.

RESULTS: The sample included 1,291 TDIs seen in a sample predominantly comprised of boys (59.8%), with a median age of 3.0 years (interquartile range 1.8-7.1 years), mostly in the deciduous dentition (71.6%) with ≥ 1 TDIs between 2010 and 2019. Accidents mainly occurred at home (45.6%) or outdoors (30.3%) and were primarily the result of falls (37.2%) or playtime (29.5%). Affected children often visited the dentist within the first 24 h (77.1%). Deciduous teeth (51.9%) and permanent teeth (37.2%; p = 0.001) primarily exhibited injuries to the periodontal tissue.

CONCLUSION: This study found boys were more prone to TDI than girls. Significant differences were seen in the injury mechanisms between deciduous and permanent teeth. Moreover, injuries to the periodontal tissue, with or without tooth fractures, were the most common trauma found.

CLINICAL RELEVANCE: Gaining insights into TDI patterns over time can help clinical practitioners develop more effective prevention measures.

PMID:40947438 | DOI:10.1007/s00784-025-06546-4

Clin Oral Investig. 2025 Sep 15;29(10):450. doi: 10.1007/s00784-025-06546-4.

ABSTRACT

OBJECTIVE: This study aimed to analyze accident-related traumatic dental injury (TDI) data to determine the occurrence, characteristics, and types of dental injuries in primary and permanent dentitions of underage patients attending a university clinic.

MATERIALS AND METHODS: A retrospective observational study was conducted at the Clinic of Orthodontics and Pediatric Dentistry of Zurich from 2010 to 2019 and involved children with accident-related TDIs from the ages of 0 to 18 years old. Data regarding patient- and trauma-related characteristics were extracted and analyzed statistically according to dentition, tooth, age, sex, and time elapsed before visiting the dentist at 5%.

RESULTS: The sample included 1,291 TDIs seen in a sample predominantly comprised of boys (59.8%), with a median age of 3.0 years (interquartile range 1.8-7.1 years), mostly in the deciduous dentition (71.6%) with ≥ 1 TDIs between 2010 and 2019. Accidents mainly occurred at home (45.6%) or outdoors (30.3%) and were primarily the result of falls (37.2%) or playtime (29.5%). Affected children often visited the dentist within the first 24 h (77.1%). Deciduous teeth (51.9%) and permanent teeth (37.2%; p = 0.001) primarily exhibited injuries to the periodontal tissue.

CONCLUSION: This study found boys were more prone to TDI than girls. Significant differences were seen in the injury mechanisms between deciduous and permanent teeth. Moreover, injuries to the periodontal tissue, with or without tooth fractures, were the most common trauma found.

CLINICAL RELEVANCE: Gaining insights into TDI patterns over time can help clinical practitioners develop more effective prevention measures.

PMID:40947438 | DOI:10.1007/s00784-025-06546-4

Eur J Epidemiol. 2025 Sep 15. doi: 10.1007/s10654-025-01296-9. Online ahead of print.

ABSTRACT

Social isolation is recognized as a public health emergency. However, major guidelines provide vastly different recommendations on how to target it, and no strategy has been substantiated on firm theoretical or empirical grounds, yet. Rose’s seminal The Strategy of Preventive Medicine provided a theoretical framework for such arbitrations between approaches. Therein, determining the shape of the relationship between risk factor and outcome is of paramount importance. However, quantitative approaches immediately applying this theory to evidence are still lacking. Thus, in this pre-registered analysis, we pursued a novel approach and employed generalized additive mixed models to model the shape of social isolation’s Links to brain, cognitive and mental health outcomes in a well-characterised population-based sample. We derived brain measures from 3T MRIs, assessed cognitive functions with extensive neuropsychological testing and measured social isolation and mental health outcomes using established questionnaires. Overall, we studied over 10,000 (mean age 58a, 53% women) participants at baseline and over 5500 (mean age 64a, 53% women) at follow-up after ~ 6 years. The relationship of social contact with almost all outcomes was firmly linear and did not differ above and below the standard threshold for social isolation. Only for processing speed did we detect a steeper slope amongst socially isolated individuals. Hence, most of the health effects of social contact were observed in individuals that would not be categorised as socially isolated. Applying advanced statistical methods to a large and well-characterised dataset we provide evidence in support of a shift in focus away from individual-level and towards population-level preventive approaches.

PMID:40947435 | DOI:10.1007/s10654-025-01296-9

Stat Med. 2025 Sep;44(20-22):e70262. doi: 10.1002/sim.70262.

ABSTRACT

With the advent of precision medicine and targeted therapies in cancer, new challenges in the statistical design of clinical trials have naturally emerged. Most randomized clinical trial designs incorporating predictive biomarkers (those associated with treatment efficacy) assume biomarkers are dichotomous, or dichotomize naturally continuous biomarkers upfront, or find cut points mid-way through the trial to classify patients as biomarker-positive or biomarker-negative. However, these practices ignore or discard information about continuous and possible nonlinear or non-monotone prognostic or predictive effects. In this article, we propose a novel adaptive enrichment trial design to handle continuous biomarkers with any effect shape, including Bayesian marker-adaptive randomization. We demonstrate that this design can correctly make marker-specific trial decisions with high efficiency, resulting in improved performance and patient-centered decisions compared to adaptive cut-point selection approaches without adaptive randomization that further ignore or oversimplify true underlying marker relationships.

PMID:40947424 | DOI:10.1002/sim.70262