Category: Nevin Manimala

Ther Innov Regul Sci. 2023 May 13. doi: 10.1007/s43441-023-00528-y. Online ahead of print.

ABSTRACT

Despite increasing utilization of real-world data (RWD)/real-world evidence (RWE) in regulatory submissions, their application to oncology drug approvals has seen limited success. Real-world data is most commonly summarized as a benchmark control for a single arm study or used to augment the concurrent control in a randomized clinical trial (RCT). While there has been substantial research on usage of RWD/RWE, our goal is to provide a comprehensive overview of their use in oncology drug approval submissions to inform future RWD/RWE study design. We will review examples of applications and summarize the strengths and weaknesses of each example identified by regulatory agencies. A few noteworthy case studies will be reviewed in detail. Operational aspects of RWD/RWE study design/analysis will be also discussed.

PMID:37179264 | DOI:10.1007/s43441-023-00528-y

Huan Jing Ke Xue. 2023 May 8;44(5):3003-3016. doi: 10.13227/j.hjkx.202205258.

ABSTRACT

Global warming and intensified human activities have led to regional climate instability with increasing frequency and the persistence of high-temperature climate events. Eco-environmental protection and socio-economic development have been faced with rigorous threats. Taking the monthly maximum temperatures from 1950 to 2019 as the basic data source, the spatial-temporal evolution characteristics of seasonal average maximum temperature (AMT) were discerned using the Mann-Kendall test and unary linear regression method in China from 1950 to 2019. Combined with linear correlation, partial linear correlation, and wavelet analysis, the correlation between seasonal AMT characteristics and atmospheric circulations was analyzed quantitatively. The results showed that:① the AMT in all seasons had a significant upward trend, with an increase of 1.21, 0.08, 1.81, and 0.25℃ in spring, summer, autumn, and winter, respectively. The abrupt change times of the AMT were concentrated in the 1990s to the early 21st century. ② In terms of spatial distribution, except for in summer, the average trend rates of AMT in other seasons increased gradually from south to north, although the increasing degrees were different. Among them, the AMT change rate in spring-winter was the fastest in northeast and northwest China. ③ There were complex correlations between the AMT of every season and atmospheric circulation factors, and the distribution of the interrelation energy varied significantly in different frequency domains. Specifically, the Pacific Decadal Oscillation had a significant negative correlation with AMT in summer. The North Atlantic Oscillation had an active effect on AMT changes in summer, autumn, and winter. The Arctic Oscillation had a significant positive driving effect on AMT in all seasons, and there were significant positive or negative influences on the short-or long-term changes of AMT in spring and summer due to the different EI Niño-Southern Oscillation years. These results could provide a theoretical basis and technical reference for China to formulate scientific and effective response plans of climate change.

PMID:37177972 | DOI:10.13227/j.hjkx.202205258

Huan Jing Ke Xue. 2023 May 8;44(5):2799-2816. doi: 10.13227/j.hjkx.202205206.

ABSTRACT

The geographical detector is a new statistical method to detect spatial stratified heterogeneity and reveal the driving factors behind it. It can not only reveal the influence of a single factor on dependent variables but also evaluate the influence of two-factor interactions and does not need to consider linearity, while also avoiding the influence of multivariate collinearity. Without strong model assumptions, it solves the limitations of traditional methods in analyzing category variables. The research on the spatial differentiation of heavy metals in soil is increasingly widely used. This study collected 40 research reports on the spatial differentiation of soil heavy metals via geographical detector, combed the discrete methods of independent variables, research scale, dependent variables and types of independent variables, factor detection, exchange detection, risk detection, and ecological detection and put forward the problems that need to be clarified in the future application of this research. It is expected to provide support for the deep application of geo-detector in the field of spatial differentiation of soil heavy metals.

PMID:37177952 | DOI:10.13227/j.hjkx.202205206

Huan Jing Ke Xue. 2023 May 8;44(5):2601-2612. doi: 10.13227/j.hjkx.202205351.

ABSTRACT

In order to study the chemical characteristics and ion source of groundwater and further serve the scientific development and management of water resources in Shunping County. A total of 33 groups of karst water and 12 groups of pore water samples were collected systematically in Shunping County, and the hydrochemical types, composition characteristics, and main controlling factors of various types of groundwater were analyzed by using Gibbs diagram, ion ratio relation, and multivariate statistical analysis methods, and the contribution rates of various sources to groundwater solutes were evaluated. The results showed that the pore water and karst water in the study area were weakly alkaline, with TDS ranging from 245.89 to 430.00 mg·L^-1 and 223.54 to 1347.80 mg·L^-1, respectively. The anion components of groundwater were mainly HCO₃^– and Ca²⁺. Groundwater in the study area could be grouped into PW1 and PW2 pore water and KW1, KW2, and KW3 karst water. PW1 and KW1 were HCO₃-Ca·Mg type, PW2 was HCO₃·Cl-Ca·Mg type, KW2 was HCO₃·NO₃-Ca·Mg type, and KW3 was SO₄-Ca·Mg type with high salinity. The weathering of carbonate rock mainly composed of dolomite and silicate rock mainly composed of albiar and potassium feldspar were the main material sources of groundwater, and their contributions to each water body were 39.69% to 66.13% and 11.87% to 58.38%. Sewage discharge and fertilizer use in human activities had significant effects on KW2 groundwater and PW1, PW2, and KW1 groundwater, respectively. In addition, the contribution rate of atmospheric precipitation to each water body ranged from 1.09% to 7.94% on average.

PMID:37177934 | DOI:10.13227/j.hjkx.202205351

J Magn Reson Imaging. 2023 May 13. doi: 10.1002/jmri.28725. Online ahead of print.

ABSTRACT

BACKGROUND: The prognosis of hepatocellular carcinoma (HCC) is difficult to predict and carries high mortality. This study utilized radiomic techniques with clinical examinations to assess recurrence in HCC.

PURPOSE: To develop a Cox nomogram to assess the risk of postoperative recurrence in HCC using radiomic features of three volumes of interest (VOIs) in preoperative dynamic contrast-enhanced MRI (DCE-MRI), along with clinical findings.

STUDY TYPE: Retrospective.

SUBJECTS: 249 patients with pathologically proven HCCs undergoing surgical resection at three institutions were selected.

FIELD STRENGTH/SEQUENCE: Fat saturated T2-weighted, Fat saturated T1-weighted, and DCE-MRI performed at 1.5 T and 3.0 T.

ASSESSMENT: Three VOIs were generated; the tumor VOI corresponds to the area from the tumor core to the outer perimeter of the tumor, the tumor +10 mm VOI represents the area from the tumor perimeter to 10 mm distal to the tumor in all directions, finally, the background liver parenchyma VOI represents the hepatic tissue outside the tumor. Three models were generated. The total radiomic model combined information from the three listed VOI’s above. The clinical-radiological model combines physical examination findings with imaging characteristics such as tumor size, margin features, and metastasis. The combined radiomic model includes features from both models listed above and showed the highest reliability for assessing 24-month survival for HCC.

STATISTICAL TESTS: The least absolute shrinkage and selection operator (LASSO) Cox regression, univariable, and multivariable Cox regression, Kmeans clustering, and Kaplan-Meier analysis. The discrimination performance of each model was quantified by the C-index. A P value <0.05 was considered statistically significant.

RESULTS: The combined radiomic model, which included features from the radiomic VOI’s and clinical imaging provided the highest performance (C-index: training cohort = 0.893, test cohort = 0.851, external cohort = 0.797) in assessing the survival of HCC.

CONCLUSION: The combined radiomic model provides superior ability to discern the possibility of recurrence-free survival in HCC over the total radiomic and the clinical-radiological models.

EVIDENCE LEVEL: 4.

TECHNICAL EFFICACY: Stage 2.

PMID:37177868 | DOI:10.1002/jmri.28725

Alzheimers Dement. 2023 May 12. doi: 10.1002/alz.13113. Online ahead of print.

ABSTRACT

INTRODUCTION: Recent genome-wide association studies identified new dementia-associated variants. We assessed the performance of updated polygenic risk scores (PRSs) using these variants in an independent cohort.

METHODS: We used Cox models and area under the curve (AUC) to validate new PRSs (PRS-83SNP, PRS-SBayesR, and PRS-CS) compared with an older PRS-23SNP in 12,031 initially-healthy participants ≥70 years of age. Dementia was rigorously adjudicated according to Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria.

RESULTS: PRS-83SNP, PRS-SBayesR, and PRS-CS were associated with incident dementia, with fully adjusted (including apolipoprotein E [APOE] ε4) hazard ratios per standard deviation (SD) of 1.35 (1.23-1.47), 1.37 (1.25-1.50), and 1.42 (1.30-1.56), respectively. The AUC of a model containing conventional/non-genetic factors and APOE was 74.7%. This was improved to 75.7% (p = 0.007), 76% (p = 0.004), and 76.1% (p = 0.003) with addition of PRS-83SNP, PRS-SBayesR, and PRS-CS, respectively. The PRS-23SNP did not improve AUC (74.7%, p = 0.95).

CONCLUSION: New PRSs for dementia significantly improve risk-prediction performance, but still account for less risk than APOE genotype overall.

PMID:37177856 | DOI:10.1002/alz.13113

J Magn Reson Imaging. 2023 May 13. doi: 10.1002/jmri.28770. Online ahead of print.

ABSTRACT

BACKGROUND: The diagnosis of prenatal placenta accreta spectrum (PAS) with magnetic resonance imaging (MRI) is highly dependent on radiologists’ experience. A deep learning (DL) method using the prior knowledge that PAS-related signs are generally found along the utero-placental borderline (UPB) may help radiologists, especially those with less experience, to mitigate this issue.

PURPOSE: To develop a DL tool for antenatal diagnosis of PAS using T2-weighted MR images.

STUDY TYPE: Retrospective.

SUBJECTS: Five hundred and forty pregnant women with clinically suspected PAS disorders from two institutions, divided into training (409), internal test (103), and external test (28) datasets.

FIELD STRENGTH/SEQUENCE: Sagittal T2-weighted fast spin echo sequence at 1.5 T and 3 T.

ASSESSMENT: An nnU-Net was trained for placenta segmentation. The UPB straightening approach was used to extract the utero-placental boundary region. The UPB image was then fed into DenseNet-PAS for PAS diagnosis. DenseNet-PP learnt placental position information to improve the PAS diagnosis performance. Three radiologists with 8, 10, and 12 years of experience independently evaluated the images. Two radiologists marked the placenta tissue. Histopathological findings were the reference standard.

STATISTICAL TESTS: Area under the curve (AUC) was used to evaluate the classification. Dice coefficient evaluated the segmentation between radiologists and the model performance. The Mann-Whitney U-test or the chi-squared test assessed the significance of differences. Decision curve analysis was used to determine clinical effectiveness. DeLong’s test was used to compare AUCs.

RESULTS: Of the 540 patients, 170 had PAS disorders confirmed by histopathology. The DL model using UPB images and placental position yielded the highest AUC of 0.860 and 0.897 in internal test and external test cohorts, respectively, significantly exceeding the performance of three radiologists (internal test AUC, 0.737-0.770).

DATA CONCLUSION: By extracting the UPB image, this fully automatic DL pipeline achieved high accuracy and may assist radiologists in PAS diagnosis using MRI.

LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

PMID:37177832 | DOI:10.1002/jmri.28770

Acta Psychiatr Scand. 2023 May 12. doi: 10.1111/acps.13568. Online ahead of print.

ABSTRACT

OBJECTIVES: The augmentation of serotonin reuptake inhibitors (SRIs) can be achieved by add-on therapy with different pharmacological agents in obsessive-compulsive disorder (OCD) for a better clinical outcome. This network meta-analysis (NMA) was conducted to evaluate and compare the effects of available augmentation agents for SRIs in OCD.

METHOD: The data was extracted from 59 relevant clinical trials after a literature search on MEDLINE/PubMed, Scopus, Cochrane databases and clinical trial registries. PRISMA guidelines were followed in data extraction, analysis and reporting. Random effects Bayesian NMA was done to pool the effects across the interventions for the change in Yale-Brown Obsessive-Compulsive Scale (YBOCS) scoring from baseline to the end of the study. Network graph was built, consistency model was run, node splitting analysis was performed, treatments were ranked as per SUCRA score and meta-regression was done for refractoriness to SRIs and duration of augmentation therapy as the predictor variables.

RESULTS: The drugs showing significant reduction in YBOCS scoring were pregabalin (MD:-8.1;95% CrI: -16, -0.43), memantine (MD:-6.2;95% CrI: -9.9, -2.3), lamotrigine (MD:-6;95% CrI: -12, -0.47), ondansetron (MD:-5.7;95% CrI: -11, -0.67), granisetron (MD:-5.6;95% CrI: -11, -0.44), aripiprazole (MD:-5.4;95% CrI:-9.1, -1.6), risperidone (MD:-3.3;95% CrI: -6.4, -0.20) and topiramate (MD:-5.3;95% CrI: -9.6, -0.97). The node-split analysis showed that direct and indirect pooled effect sizes for all comparisons were comparable. Meta-regression showed a statistically non-significant association between YBOCS score reduction with the duration of augmentation therapy, but significant with SRI-refractory status. Finally, the results were sorted based on certainty of evidence.

CONCLUSION: Memantine was found to be most effective augmentation agent for SRIs in OCD, followed by lamotrigine, ondansetron and granisetron with moderate certainty of evidence. The augmentation agents showed better symptom reduction in patients with SRI-refractory OCD in comparison to non-refractory OCD.

PROSPERO REGISTRATION: CRD42022360110.

PMID:37177823 | DOI:10.1111/acps.13568

Int J Gynaecol Obstet. 2023 May 13. doi: 10.1002/ijgo.14835. Online ahead of print.

ABSTRACT

OBJECTIVE: To describe and compare the annual success rates of medical treatment in the analyzed period and to evaluate the associated factors.

METHODS: Retrospective study with 158 women with tubal pregnancy followed up over 17 years. Statistical analysis was performed using the Cochran-Armitage test, the χ² test, Mann-Whitney test, and multiple logistic regression.

RESULTS: The success rate was 47.4%. There was a trend of significant change in the success rate of clinical treatment over time (Z = 2.01, P = 0.044); it was associated to undergoing treatment between 2012 and 2017 (P = 0.028), the absence of abdominal pain (P = 0.020), receiving a higher dose of methotrexate (P < 0.001), and less time hospitalized (P < 0.001). In the final statistical model, we observed that receiving a higher dose of methotrexate (P = 0.025, odds ratio [OR] 1.03, 95% confidence interval [CI] 1.00-1.06), having a low serum β-HCG concentration before treatment (P = 0.003, OR 0.87, 95% CI 0.79-0.95), and not having abdominal pain (P = 0.004, OR 4.26, 95% CI 1.61-11.28) were factors associated with a higher chance of successful clinical treatment for tubal pregnancy.

CONCLUSION: A greater chance of success was observed among women undergoing clinical treatment from 2012 onwards, who used higher doses of methotrexate, were asymptomatic at admission, and had low concentrations of β-hCG.

PMID:37177821 | DOI:10.1002/ijgo.14835

Ann Bot. 2023 May 13:mcad047. doi: 10.1093/aob/mcad047. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: Hybridization has long been recognized as an important process for plant evolution and is often accompanied by polyploidization, another prominent force in generating biodiversity. Despite its pivotal importance in evolution, the actual prevalence and distribution of hybridization across the tree of life remain unclear.

METHODS: We used whole-genome shotgun (WGS) sequencing and cytological data to investigate the evolutionary history of Henckelia, a large genus in the family Gesneriaceae with a high frequency of suspected hybridization and polyploidization events. We generated WGS sequencing data at about 10× coverage for 26 Chinese Henckelia species plus one Sri Lanka species. To untangle the hybridization history, we separately extracted whole plastomes and thousands of single-copy nuclear genes from the sequencing data, and reconstructed phylogenies based on both nuclear and plastid data. We also explored sources of both genealogical and cytonuclear conflicts and identified signals of hybridization and introgression within our phylogenomic dataset using several statistical methods. Additionally, to test the polyploidization history, we evaluated chromosome counts for 45 populations of the studied 27 Henckelia species.

KEY RESULTS: We obtained well-supported phylogenetic relationships using both concatenation and coalescent-based methods. However, the nuclear phylogenies were highly inconsistent with the plastid phylogeny, and we observed intensive discordance among nuclear gene trees. Further analyses suggested that both incomplete lineage sorting (ILS) and gene flow contributed to the observed cytonuclear and genealogical discordance. Our analyses of introgression and phylogenetic networks revealed a complex history of hybridization within the genus Henckelia. In addition, based on chromosome counts for 27 Henckelia species, we found independent polyploidization events occurred within Henckelia after different hybridization events.

CONCLUSIONS: Our findings demonstrated that hybridization and polyploidization are common in Henckelia. Furthermore, our results revealed that H. oblongifolia is not a member of the redefined Henckelia and suggested several other taxonomic treatments in this genus.

PMID:37177810 | DOI:10.1093/aob/mcad047