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Nevin Manimala Statistics

Integrated Multimodal Analyses of DNA Damage Response and Immune Markers as Predictors of Response in Metastatic Triple-Negative Breast Cancer in the TNT Trial (NCT00532727)

Clin Cancer Res. 2023 Aug 14:OF1-OF15. doi: 10.1158/1078-0432.CCR-23-0370. Online ahead of print.

ABSTRACT

PURPOSE: The TNT trial (NCT00532727) showed no evidence of carboplatin superiority over docetaxel in metastatic triple-negative breast cancer (mTNBC), but carboplatin benefit was observed in the germline BRCA1/2 mutation subgroup. Broader response-predictive biomarkers are needed. We explored the predictive ability of DNA damage response (DDR) and immune markers.

PATIENTS AND METHODS: Tumor-infiltrating lymphocytes were evaluated for 222 of 376 patients. Primary tumors (PT) from 186 TNT participants (13 matched recurrences) were profiled using total RNA sequencing. Four transcriptional DDR-related and 25 immune-related signatures were evaluated. We assessed their association with objective response rate (ORR) and progression-free survival (PFS). Conditional inference forest clustering was applied to integrate multimodal data. The biology of subgroups was characterized by 693 gene expression modules and other markers.

RESULTS: Transcriptional DDR-related biomarkers were not predictive of ORR to either treatment overall. Changes from PT to recurrence were demonstrated; in chemotherapy-naïve patients, transcriptional DDR markers separated carboplatin responders from nonresponders (P values = 0.017; 0.046). High immune infiltration was associated with docetaxel ORR (interaction P values < 0.05). Six subgroups were identified; the immune-enriched cluster had preferential docetaxel response [62.5% (D) vs. 29.4% (C); P = 0.016]. The immune-depleted cluster had preferential carboplatin response [8.0% (D) vs. 40.0% (C); P = 0.011]. DDR-related subgroups were too small to assess ORR.

CONCLUSIONS: High immune features predict docetaxel response, and high DDR signature scores predict carboplatin response in treatment-naïve mTNBC. Integrating multimodal DDR and immune-related markers identifies subgroups with differential treatment sensitivity. Treatment options for patients with immune-low and DDR-proficient tumors remains an outstanding need. Caution is needed using PT-derived transcriptional signatures to direct treatment in mTNBC, particularly DDR-related markers following prior chemotherapy.

PMID:37574209 | DOI:10.1158/1078-0432.CCR-23-0370

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Nevin Manimala Statistics

Safety and Efficacy of Turmeric (Curcuma longa) Extract and Curcumin Supplements in Musculoskeletal Health: A Systematic Review and Meta-Analysis

Altern Ther Health Med. 2023 Sep;29(6):12-24.

ABSTRACT

CONTEXT: Turmeric is a well-known herb that has been used in many traditional medicinal systems since ancient times. Turmeric roots contain hydrophobic polyphenols called curcuminoids, which have proven anti-inflammatory and antioxidant effects and are shown to be beneficial for the management of musculoskeletal health. Various products containing curcumin or turmeric extract are commercially available.

OBJECTIVE: This systematic review and meta-analysis of randomized clinical trials (RCTs) is intended to evaluate the effective dose, safety, and efficacy of commercial turmeric extract and curcumin supplements in musculoskeletal health.

DESIGN: The research team performed a systematic literature search of PubMed, Google Scholar, and Cochrane Library databases and conducted a meta-analysis according to PRISMA guidelines.

SETTING: Authors from India and USA contributed to this systematic review and meta-analysis.

RESULTS: The research team analyzed 21 prospective, randomized clinical studies, of which seven studies were focused on skeletal muscle health and fourteen on joint health. Statistical heterogeneity was established based on the results of heterogeneity analysis of a Chi-square (χ2) value for Cochran’s Q statistic of 29.3765 for musculoskeletal and 3666.80 for joint health studies (P < .0001 for both analyses). Therefore, the random effects model was used. The χ2 value of the random effects model was 216.5545 for skeletal muscle health studies and 1400.65 for joint health studies, which was statistically significant with P < .0001 for both analyses.

CONCLUSIONS: Turmeric extract and curcumin supplements can be effective adjuvants for the management of musculoskeletal health, with a low incidence of AEs. The water-dispersible turmeric extract, WDTE60N, at a dose of 250 mg per day, was found to be more effective than other curcumin products. However, the studies included in the analysis were conducted using diverse doses and treatment durations. Further evaluation using comparisons in future clinical trials can establish the appropriate effective dose of curcumin supplements for the overall maintenance of musculoskeletal health.

PMID:37574203

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Nevin Manimala Statistics

Evaluating predictors of successful postoperative day 1 discharge following posterior fossa tumor resection

World Neurosurg. 2023 Aug 11:S1878-8750(23)01119-1. doi: 10.1016/j.wneu.2023.08.017. Online ahead of print.

ABSTRACT

BACKGROUND: Current trends in surgical neuro-oncology show that early discharges are safe and feasible with shorter lengths of stay (LOS) and fewer thromboembolic complications, fewer hospital-acquired infections, reduced costs, and greater patient satisfaction. Traditionally, infratentorial tumor resections have been associated with longer LOS and limited data exists evaluating predictors of early discharge in these patients. The objective was to assess patients undergoing posterior fossa craniotomies for tumor resection and identify variables associated with postoperative day 1 (POD1) discharge.

METHODS: A retrospective review of posterior fossa craniotomies for tumor resection at our institution was performed from 2011 to 2020. Laser ablations, non-tumoral pathologies, and biopsies were excluded. Demographic, clinical, surgical, and postoperative data were collected.

RESULTS: 173 patients were identified and 25 (14.5%) were discharged on POD1. Median length of stay was 6 days. The POD1 discharges had significantly better preoperative Karnofsky performance scores (p<0.001) and modified Rankin scores (p=0.002) and more frequently presented electively (p=0.006) and without preoperative neurologic deficits (p=0.021). No statistically significant difference in 30-day readmissions and rates of PE, UTI, and DVT was found. Univariate logistic regression identified better preoperative functional status, elective admission, and lack of preoperative hydrocephalus as predictors of POD1 discharge, however only the latter remained significant in the multivariable model (p=0.001).

CONCLUSIONS: Discharging patients on POD1 is feasible following posterior fossa tumor resection in a select group of patients. Although we found that the only independent predictor for a longer LOS was preoperative hydrocephalus, larger, prospective studies are needed to confirm these findings.

PMID:37574194 | DOI:10.1016/j.wneu.2023.08.017

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Nevin Manimala Statistics

Baseline Frailty and Discharge to Advanced Care Facilities In Patients Undergoing Lumbar Interbody Fusion for Lumbar Degenerative Disease: A Multicenter Registry Analysis of 7153 Patient Cases Comparing the Risk Analysis Index to the 5-Factor Modified Frailty Index

World Neurosurg. 2023 Aug 11:S1878-8750(23)01131-2. doi: 10.1016/j.wneu.2023.08.027. Online ahead of print.

ABSTRACT

OBJECTIVE: To evaluate the impact of frailty, as measured by the 5-factor Modified Frailty Index (mFI-5) and the Risk Analysis Index (RAI), on advanced care facility discharge (FD) in patients who underwent lumbar fusion for lumbar degenerative spine disease.

METHODS: The American College of Surgeons National Surgical Quality Improvement Program (2012-2020) was queried for adults (≥18 years) undergoing lumbar fusion for LDD. Descriptive statistics and univariate crosstabulation were used to assess baseline demographics, preoperative comorbidities, and postoperative outcomes. Receiver operating characteristic (ROC) curve analysis was used to assess the discriminative threshold of the mFI-5 and RAI on FD within this population.

RESULTS: The median patient age in this study cohort (N=7153) was 56 years and FD occurred in 7.3% of cases. ROC curve analysis demonstrated that both the mFI-5 and the RAI accurately predicted FD (C-statistics: mFI-5: 0.627; RAI: 0.746). DeLong’s test found that the RAI had superior discrimination when compared to the mFI-5 (P<0.0001).

CONCLUSIONS: RAI is a reliable predictor of FD in LDD patients who underwent LIF and demonstrated superior discrimination compared to the mFI-5. Identification of patients at risk for FD may facilitate more precise risk stratification to enable better preoperative decision-making and help set more realistic expectations of care.

PMID:37574193 | DOI:10.1016/j.wneu.2023.08.027

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Nevin Manimala Statistics

Traditional machine learning methods vs. deep learning for meningioma classification, grading, outcome prediction, and segmentation: a systematic review and meta-analysis

World Neurosurg. 2023 Aug 11:S1878-8750(23)01126-9. doi: 10.1016/j.wneu.2023.08.023. Online ahead of print.

ABSTRACT

BACKGROUND: Meningiomas are common intracranial tumors. Machine learning (ML) algorithms are emerging to improve accuracy in four primary domains: classification, grading, outcome prediction, and segmentation. Such algorithms include both, traditional approaches that rely on hand-crafted features and deep learning techniques that utilize automatic feature extraction.

OBJECTIVE: To evaluate the performance of published traditional ML vs. deep learning algorithms in classification, grading, outcome prediction, and segmentation of meningiomas.

METHODS: A systematic review and meta-analysis were conducted. Major databases were searched through September 2021 for publications evaluating traditional ML vs. deep learning models on meningioma management. Performance measures including pooled sensitivity, specificity, F1-score, area under the receiver-operating characteristic curve (AUC), positive and negative likelihood ratios (LR+, LR-) along with their respective 95% confidence intervals (95%CIs) were derived using random-effects models.

RESULTS: 534 records were screened, and 43 articles were included, regarding classification (3 articles), grading (29), outcome prediction (7), and segmentation (6) of meningiomas. Of the 29 studies that reported on grading, 10 could be meta-analyzed with two deep learning models (sensitivity 0.89, 95%CI 0.74-0.96; specificity 0.91, 95%CI 0.45-0.99; LR+ 10.1, 95%CI 1.33-137; LR- 0.12, 95%CI 0.04-0.59) and eight traditional ML (sensitivity 0.74, 95%CI 0.62-0.83; specificity 0.93, 95%CI 0.79-0.98; LR+ 10.5, 95%CI 2.91-39.5; and LR- 0.28, 95%CI 0.17-0.49). The insufficient performance metrics reported precluded further statistical analysis of other performance metrics.

CONCLUSION: Machine learning on meningiomas is mostly carried out with traditional methods. For meningioma grading, traditional machine learning methods generally had a higher LR+, while deep learning models a lower LR-.

PMID:37574189 | DOI:10.1016/j.wneu.2023.08.023

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Nevin Manimala Statistics

The Pain Anxiety Symptom Scale: Initial development and evaluation of four and eight item short forms

J Pain. 2023 Aug 11:S1526-5900(23)00496-0. doi: 10.1016/j.jpain.2023.08.001. Online ahead of print.

ABSTRACT

Elevated levels of anxiety in relation to chronic pain have been consistently associated with greater distress and disability. Thus, accurate measurement of pain-related anxiety is an important requirement in modern pain services. The Pain Anxiety Symptom Scale (PASS) was introduced over 30 years ago, with a shortened 20 item version introduced 10 years later. Both versions of the PASS were derived using principal components analysis, an established method of measure development with roots in classical test theory. Item Response Theory is a complementary approach to measure development that can reduce the number of items needed and maximize item utility with minimal loss of statistical and clinical information. The present study used IRT to shorten the 20 item PASS (PASS-20) in a large sample of people with chronic pain (N = 2669). Two shortened versions were evaluated, one composed of the single best performing item from each of its four subscales (PASS-4) and the other with the two best performing items from each subscale (PASS-8). Several supplementary analyses were performed, including comparative item convergence evaluations based on sample characteristics (i.e., female/male sex; clinical/online sample), factor invariance testing, and criterion validity evaluation of the 4, 8, and 20 item version of the PASS in hierarchical regression models predicting pain-related distress and interference. Overall, both shortened PASS versions performed adequately across these supplemental tests, although the PASS-4 had more consistent item convergence between samples, stronger evidence for factor invariance, and accounted for 83% of the variance accounted for by the PASS-20 and 92% of the variance accounted for by the PASS-8 in criterion variables. Consequently, the PASS-4 is recommended for use in situations where a briefer evaluation of pain-related anxiety is appropriate. PERSPECTIVE: The Pain Anxiety Symptom Scale (PASS) is an established measure of pain-related fear. This study derived four and eight item versions of the PASS using Item Response Theory. Both versions showed strong psychometric properties, stability of factor structure, and relation to important aspects of pain-related functioning.

PMID:37574179 | DOI:10.1016/j.jpain.2023.08.001

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Nevin Manimala Statistics

Brigatinib Versus Alectinib in ALK-positive Non-small Cell Lung Cancer After Disease Progression on Crizotinib: Results of Phase 3 ALTA-3 Trial

J Thorac Oncol. 2023 Aug 11:S1556-0864(23)00730-X. doi: 10.1016/j.jtho.2023.08.010. Online ahead of print.

ABSTRACT

INTRODUCTION: This open-label, phase 3 trial (ALTA-3; NCT03596866) compared efficacy and safety of brigatinib versus alectinib for ALK+ NSCLC after disease progression on crizotinib.

METHODS: Patients with advanced ALK+ NSCLC that progressed on crizotinib were randomized 1:1 to brigatinib 180 mg once daily (7-day lead-in, 90 mg) or alectinib 600 mg twice daily, aiming to test superiority. The primary endpoint was blinded independent review committee (BIRC)-assessed progression-free survival (PFS). Interim analysis for efficacy and futility was planned at approximately 70% of 164 expected PFS events.

RESULTS: The population (N=248; brigatinib, n=125; alectinib, n=123) was notable for long median duration of prior crizotinib (16.0-16.8 months) and low rate of ALK fusion in baseline circulating tumor DNA (ctDNA; 78/232 [34%]). Median BIRC-assessed PFS was 19.3 months with brigatinib and 19.2 months with alectinib (hazard ratio: 0.97 [95% confidence interval [CI]: 0.66-1.42]; p=0.8672]). The study met futility criterion. Overall survival was immature (41 events [17%]). Exploratory analyses pooled across treatment groups demonstrated median PFS of 11.1 versus 22.5 months in patients with versus without ctDNA-detectable ALK fusion at baseline (hazard ratio: 0.48 [95% CI: 0.32-0.71]). Treatment-related adverse events in >30% of patients (brigatinib/alectinib) were elevated blood creatine phosphokinase (70%/29%), aspartate aminotransferase (53%/38%), and alanine aminotransferase (40%/36%).

CONCLUSION: Brigatinib was not superior to alectinib for PFS in crizotinib-pretreated ALK+ NSCLC. Safety was consistent with the well-established and unique profiles of each drug. The low proportion of patients with ctDNA-detectable ALK fusion may account for prolonged PFS with both drugs in ALTA-3.

PMID:37574132 | DOI:10.1016/j.jtho.2023.08.010

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Nevin Manimala Statistics

Non-proportional hazards demystified: Why they matter for planning and interpreting clinical trials

Can J Cardiol. 2023 Aug 11:S0828-282X(23)01582-9. doi: 10.1016/j.cjca.2023.08.008. Online ahead of print.

NO ABSTRACT

PMID:37574131 | DOI:10.1016/j.cjca.2023.08.008

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Nevin Manimala Statistics

Multivariate prediction of cognitive performance from the sleep electroencephalogram

Neuroimage. 2023 Aug 11:120319. doi: 10.1016/j.neuroimage.2023.120319. Online ahead of print.

ABSTRACT

Human cognitive performance is a key function whose biological foundations have been partially revealed by genetic and brain imaging studies. The sleep electroencephalogram (EEG) is tightly linked to structural and functional features of the central nervous system and serves as another promising biomarker. We used data from MrOS, a large cohort of older men and cross-validated regularized regression to link sleep EEG features to cognitive performance in cross-sectional analyses. In independent validation samples 2.5-10% of variance in cognitive performance can be accounted for by sleep EEG features, depending on the covariates used. Demographic characteristics accounted for more covariance between sleep EEG and cognition than health variables, and consequently reduced this association by a greater degree, but even with the strictest covariate sets a statistically significant association was present. Sigma power in NREM and beta power in REM sleep were associated with better cognitive performance, while theta power in REM sleep was associated with worse performance, with no substantial effect of coherence and other sleep EEG metrics. Our findings show that cognitive performance is associated with the sleep EEG (r=0.283), with the strongest effect ascribed to spindle-frequency activity. This association becomes weaker after adjusting for demographic (r=0.186) and health variables (r=0.155), but its resilience to covariate inclusion suggest that it also partially reflects trait-like differences in cognitive ability.

PMID:37574121 | DOI:10.1016/j.neuroimage.2023.120319

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Nevin Manimala Statistics

Quantitative MRI reveals widespread, network-specific myelination change during generalized epilepsy progression

Neuroimage. 2023 Aug 11:120312. doi: 10.1016/j.neuroimage.2023.120312. Online ahead of print.

ABSTRACT

Activity-dependent myelination is a fundamentally important mode of brain plasticity which significantly influences function. We recently discovered that absence seizures, which occur in multiple forms of generalized epilepsy, can induce activity-dependent myelination, which in turn promotes further progression of epilepsy. Structural alterations of myelin are likely to be widespread, given that absence seizures arise from an extensive thalamocortical network involving frontoparietal regions of the bilateral hemispheres. However, the temporal course and spatial extent of myelin plasticity is unknown, due to limitations of gold-standard histological methods such as electron microscopy (EM). In this study, we leveraged magnetization transfer and diffusion MRI for estimation of g-ratios across major white matter tracts in a mouse model of generalized epilepsy with progressive absence seizures. Electron microscopy was performed on the same brains after MRI. After seizure progression, we found increased myelination (decreased g-ratios) throughout the anterior portion (genu-to-body) of the corpus callosum but not in the posterior portion (body-splenium) nor in the fornix or the internal capsule. Curves obtained from averaging g-ratio values at every longitudinal point of the corpus callosum were statistically different with p<0.0001. Seizure-associated myelin differences found in the corpus callosum body with MRI were statistically significant (p = 0.0027) and were concordant with EM in the same region (p = 0.01). Notably, these differences were not detected by diffusion tensor imaging. This study reveals widespread myelin structural change that is specific to the absence seizure network.Furthermore, our findings demonstrate the potential utility and importance of MRI-based g-ratio estimation to non-invasively detect myelin plasticity.

PMID:37574120 | DOI:10.1016/j.neuroimage.2023.120312