Nevin Manimala

J Clin Oncol. 2024 Jun 6:JCO2301978. doi: 10.1200/JCO.23.01978. Online ahead of print.

ABSTRACT

PURPOSE: Artificial intelligence can reduce the time used by physicians on radiological assessments. For ¹⁸F-fluorodeoxyglucose-avid lymphomas, obtaining complete metabolic response (CMR) by end of treatment is prognostic.

METHODS: Here, we present a deep learning-based algorithm for fully automated treatment response assessments according to the Lugano 2014 classification. The proposed four-stage method, trained on a multicountry clinical trial (ClinicalTrials.gov identifier: NCT01287741) and tested in three independent multicenter and multicountry test sets on different non-Hodgkin lymphoma subtypes and different lines of treatment (ClinicalTrials.gov identifiers: NCT02257567, NCT02500407, 20% holdout in ClinicalTrials.gov identifier: NCT01287741), outputs the detected lesions at baseline and follow-up to enable focused radiologist review.

RESULTS: The method’s response assessment achieved high agreement with the adjudicated radiologic responses (eg, agreement for overall response assessment of 93%, 87%, and 85% in ClinicalTrials.gov identifiers: NCT01287741, NCT02500407, and NCT02257567, respectively) similar to inter-radiologist agreement and was strongly prognostic of outcomes with a trend toward higher accuracy for death risk than adjudicated radiologic responses (hazard ratio for end of treatment by-model CMR of 0.123, 0.054, and 0.205 in ClinicalTrials.gov identifiers: NCT01287741, NCT02500407, and NCT02257567, compared with, respectively, 0.226, 0.292, and 0.272 for CMR by the adjudicated responses). Furthermore, a radiologist review of the algorithm’s assessments was conducted. The radiologist median review time was 1.38 minutes/assessment, and no statistically significant differences were observed in the level of agreement of the radiologist with the model’s response compared with the level of agreement of the radiologist with the adjudicated responses.

CONCLUSION: These results suggest that the proposed method can be incorporated into radiologic response assessment workflows in cancer imaging for significant time savings and with performance similar to trained medical experts.

PMID:38843483 | DOI:10.1200/JCO.23.01978

JCO Glob Oncol. 2024 Jun;10:e2400068. doi: 10.1200/GO.24.00068.

ABSTRACT

PURPOSE: Germline genetic testing (GGT) significantly affects cancer care. While universal testing has been studied in Western societies, less is known about adoption elsewhere.

MATERIALS AND METHODS: In this study, 3,319 unselected, pan-cancer Jordanian patients diagnosed between April 2021 and September 2022 received GGT. Pathogenic germline variant (PGV) frequency among patients who were in-criteria (IC) or out-of-criteria (OOC; 2020 National Comprehensive Cancer Network criteria) and changes in clinical management in response to GGT results were evaluated. Statistical analysis was performed using two-tailed Fisher’s exact test with significance level P < .05.

RESULTS: The cohort was predominantly female (69.9%), with a mean age of 53.7 years at testing, and 53.1% were IC. While patients who were IC were more likely than patients who were OOC to have a PGV (15.8% v 9.6%; P < .0001), 149 (34.8%) patients with PGVs were OOC. Clinical management recommendations in response to GGT, including changes to treatment and/or follow-up, were made for 57.3% (161 of 281) of patients with high- or moderate-risk PGVs, including 26.1% (42 of 161) of patients who were OOC.

CONCLUSION: Universal GGT of patients with newly diagnosed cancer was successfully implemented in Jordan and led to identification of actionable PGVs that would have been missed with guidelines-based testing.

PMID:38843472 | DOI:10.1200/GO.24.00068

J Clin Oncol. 2024 Jun 6:JCO2301566. doi: 10.1200/JCO.23.01566. Online ahead of print.

ABSTRACT

PURPOSE: First-line therapy options in advanced cholangiocarcinoma (CCA) are based on the ABC-02 trial regimen (gemcitabine/cisplatin [G/C]). The NIFE trial examined nanoliposomal irinotecan/fluorouracil/leucovorin (nal-IRI/FU/LV) as alternative first-line therapy in advanced CCA.

METHODS: NIFE is a prospective, open-label, randomized, multicenter phase II study that aimed at detecting efficacy comparable with the standard treatment. Patients with advanced CCA were randomly assigned (1:1) to receive nal-IRI/FU/LV (arm A) or G/C (arm B). Stratification parameters were intrahepatic versus extrahepatic CCA, sex, and Eastern Cooperative Oncology Group (ECOG; 0/1). Arm A was designed as a Simon’s optimal two-stage design and arm B served as a randomized control group. The primary goal was to exclude an inferior progression-free survival (PFS) at 4 months of only 40%, while assuming a rate of 60% on G/C population.

RESULTS: Between 2018 and 2020, overall 91 patients were randomly assigned to receive nal-IRI/FU/LV (n = 49) or G/C (n = 42). The NIFE trial formally met its primary end point with a 4-month PFS rate of 51% in patients receiving nal-IRI/FU/LV. The median PFS was 6 months (2.4-9.6) in arm A and 6.9 months (2.5-7.9) in arm B. Median overall survival (OS) was 15.9 months (10.6-20.3) in arm A and 13.6 months (6.5-17.7) in arm B. The exploratory comparison of study arms suggested a numerical but statistically not significant advantage for nal-IRI/FU/LV (hazard ratio for PFS, 0.85 [95% CI, 0.53 to 1.38] and for OS, 0.94 [95% CI, 0.58 to 1.50]). Analysis for stratification parameters revealed no differences for sex and ECOG, but for tumor localization. The objective response rate was 24.5% with nal-IRI/FU/LV and 11.9% with G/C. No unexpected toxicities occurred. AEs related to nal-IRI/FU/LV were mainly GI and to G/C hematologic.

CONCLUSION: Treatment of advanced CCA with nal-IRI/FU/LV demonstrated efficacy in first-line therapy without new safety findings and merits further validation.

PMID:38843469 | DOI:10.1200/JCO.23.01566

ACS Sens. 2024 Jun 6. doi: 10.1021/acssensors.4c00488. Online ahead of print.

ABSTRACT

An integrated approach combining surface-enhanced Raman spectroscopy (SERS) with a specialized deep learning algorithm to rapidly and accurately detect and quantify SARS-CoV-2 variants is developed based on an angiotensin-converting enzyme 2 (ACE2)-functionalized AgNR@SiO₂ array SERS sensor. SERS spectra with concentrations of different variants were collected using a portable Raman system. After appropriate spectral preprocessing, a deep learning algorithm, CoVari, is developed to predict both the viral variant species and concentrations. Using a 10-fold cross-validation strategy, the model achieves an average accuracy of 99.9% in discriminating between different virus variants and R² values larger than 0.98 for quantifying viral concentrations of the three viruses, demonstrating the high quality of the detection. The limit of detection of the ACE2 SERS sensor is determined to be 10.472, 11.882, and 21.591 PFU/mL for SARS-CoV-2, SARS-CoV-2 B1, and CoV-NL63, respectively. The feature importance of virus classification and concentration regression in the CoVari algorithm are calculated based on a permutation algorithm, which showed a clear correlation to the biochemical origins of the spectra or spectral changes. In an unknown specimen test, classification accuracy can achieve >90% for concentrations larger than 781 PFU/mL, and the predicted concentrations consistently align with actual values, highlighting the robustness of the proposed algorithm. Based on the CoVari architecture and the output vector, this algorithm can be generalized to predict both viral variant species and concentrations simultaneously for a broader range of viruses. These results demonstrate that the SERS + CoVari strategy has the potential for rapid and quantitative detection of virus variants and potentially point-of-care diagnostic platforms.

PMID:38843447 | DOI:10.1021/acssensors.4c00488

J Clin Psychol. 2024 Jun 6. doi: 10.1002/jclp.23726. Online ahead of print.

ABSTRACT

OBJECTIVE: We aim to uncover the hot topics and development trends in clinical psychology research in the United States.

METHOD: Utilizing bibliometric analysis, we examined clinical psychology papers published in the United States from 2010 to 2022 in the Web of Science database, employing citation analysis, content analysis, author analysis, and journal analysis.

RESULTS: Our analysis revealed a significant increase in clinical psychology research, notably catalyzed by the 2019 COVID-19 pandemic. This surge was particularly evident in studies addressing mental disorders such as PTSD, anxiety, and suicidal behaviors, as well as psychological trauma related to issues like family conflict, elder abuse, and collective trauma. Furthermore, there was a distinct shift towards studying diverse populations, including gender and racial minorities, mothers, and adolescents. Therapeutic approaches, such as mindfulness-based practices and AI-assisted technologies, also gained prominence.

CONCLUSIONS: This study represents the first large-scale bibliometric analysis in the field of clinical psychology in the United States. Our findings suggest that the COVID-19 pandemic highlights the importance of studying psychological issues linked to major events. Also, researchers are increasingly focusing on minority groups. This trend, along with the use of new technologies like big data and artificial intelligence, guides future research in clinical psychology.

PUBLIC HEALTH SIGNIFICANCE STATEMENT: The works in this review suggest that the changing landscape of clinical psychology, especially post-COVID-19. The increased research post-pandemic emphasizes addressing psychological trauma arising from societal issues like family conflicts, elder abuse, and collective trauma. A positive shift towards inclusivity is evident in research, focusing on diverse groups like gender minorities, racial minorities, mothers, and adolescents. Additionally, the amplified focus on mental disorders like PTSD, anxiety, and suicidal behaviors during the pandemic stresses the need for tailored interventions and support systems. Exploring innovative methods such as mindfulness-based practices and AI-assisted technologies showcases the field’s adaptability in mental health interventions.

PMID:38843433 | DOI:10.1002/jclp.23726

Altern Ther Health Med. 2024 Jun 7:AT11238. Online ahead of print.

ABSTRACT

BACKGROUND: Diabetes, especially Type-2 diabetes mellitus (T2DM), poses a significant global health challenge. Complementary and alternative medicine, such as Unani Medicine, has gained popularity for managing T2DM.

OBJECTIVE: This systematic review aims to evaluate the efficacy and safety of Unani medications in T2DM management.

METHODS: A comprehensive literature search was conducted across multiple electronic databases to identify relevant clinical trials. Inclusion criteria focused on original research articles examining the efficacy and safety of Unani medications in patients with T2DM. Data extraction and quality assessment were performed using established criteria, and meta-analyses were conducted to assess the efficacy of Unani medications on glycemic control.

RESULTS: Five randomized controlled trials met the inclusion criteria. Meta-analyses revealed that Unani medications significantly reduced fasting blood glucose and postprandial blood glucose levels compared to control groups. However, the impact on HbA1c levels was not statistically significant. No adverse effects were reported.

CONCLUSION: The findings of this review suggest that Unani medications hold promise in the management of T2DM, as evidenced by significant reductions in fasting and postprandial blood glucose levels. However, further investigation, particularly focusing on compounds like Qurs Gulnar, is essential to unravel their mechanisms and ascertain their long-term efficacy. Moreover, enhancing study quality would provide valuable insights into the role of Unani Medicine as a complementary or alternative therapy for T2DM. These efforts are critical for establishing Unani Medicine’s place in the comprehensive management of T2DM.

PMID:38843419

Altern Ther Health Med. 2024 Jun 7:AT10359. Online ahead of print.

ABSTRACT

OBJECTIVE: This study aims to investigate the efficacy of an Internet Plus-oriented 5A home care model in managing complications arising from tumor immunotherapy among patients in the post-epidemic era. Specifically, the study focuses on skin toxicity and gastrointestinal toxicity in patients undergoing tumor immunotherapy.

METHODS: Between January 2022 and March 2023, 80 patients experiencing skin and gastrointestinal toxicities post-tumor immunotherapy in Zhangjiagang Traditional Chinese Medicine Hospital were selected. The patients were divided into two groups: a control group and an experimental group, each comprising 40 patients. The control group received traditional routine nursing and a telephone follow-up strategy. In contrast, the experimental group was introduced to a 5A home care model guided by Internet Plus, involving five key stages of implementation. Nurses utilized the Internet Plus platform to provide timely responses to patient queries and concerns. After the intervention, skin and gastrointestinal toxicity grades were assessed on days 0, 7, 14, and 21. Additionally, the completion rates of immunotherapy follow-up were compared between the two groups.

RESULTS: At day 0, there was no statistically significant difference in skin and gastrointestinal toxicity grades between the two groups (P > .05). However, on days 7, 14, and 21, both groups showed improvements compared to day 0, with the experimental group exhibiting significantly better outcomes and lower toxicity grades than the control group (RR: 0.667, 95% CI (-1.204, 0.394)). The completion rate of immunotherapy in the experimental group (97.5%) was significantly higher than that in the control group (77.5%), with a notable statistical difference (RR:1.258, 95%CI (-0.258, 0.722), P = .004). In the control group, 4 patients refused treatment, and 4 voluntarily terminated treatment, whereas only 1 patient in the experimental group voluntarily terminated treatment.

CONCLUSION: In conclusion, the Internet Plus-oriented 5A home care model enhances patient outcomes, demonstrating improved skin and gastrointestinal toxicities and a higher completion rate of immunotherapy compared to traditional nursing approaches. This model offers a more convenient and personalized health management approach, providing valuable insights for the clinical practice and future advancement of tumor immunotherapy.

PMID:38843414

Am J Drug Alcohol Abuse. 2024 Jun 6:1-11. doi: 10.1080/00952990.2024.2344482. Online ahead of print.

ABSTRACT

Background: This study explored the increased quantity and frequency of alcohol use in the American Indian (AI) population during the COVID-19 pandemic.Objectives: The aims of this study were to explore possible associations between covariables and both binge drinking and alcohol consumption during COVID-19.Methods: This cross-sectional survey study analyzed data from a sample of AI individuals (63% female) residing in California (n = 411) and Oklahoma (n = 657) between October 2020-January 2021. Analysis included summary statistics and multivariable logistic regression, including a variety of socio-economic, COVID-19 concern, and tobacco and marijuana use variables.Results: One or more alcohol binge episodes were reported between October 2020-January 2021 in 19.3% of participants and elevated overall alcohol consumption was reported by 21.6% of participants. Higher odds of elevated alcohol consumption occurred in women and those following more social distancing measures. The odds of binge drinking or elevated alcohol consumption in those using both marijuana and tobacco (aOR/ adjusted odds ratio:18.9, 95% CI = 8.5, 42.2, and aOR:3.9, 95% CI = 1.7, 8.6, respectively) were higher compared to those using neither. Similarly, the odds of binge drinking or elevated alcohol consumption in those using tobacco only (aOR:4.7, 95% CI = 2.9, 7.7 and aOR: 2.0, 95% CI = 1.1, 3.5, respectively) were higher compared to those using neither.Conclusions: This study found high rates of alcohol use and bingeing during the COVID-19 pandemic. Offering collaborative, culturally sensitive, and affordable support services are important components of intervention and preparation for future stressful events on local, as well as global levels.

PMID:38843382 | DOI:10.1080/00952990.2024.2344482

J Bone Miner Res. 2024 Jun 6:zjae082. doi: 10.1093/jbmr/zjae082. Online ahead of print.

ABSTRACT

Although the negative association of tobacco smoking with osteoporosis is well-documented, little is known regarding the shared genetic basis underlying these conditions. In this study, we aim to investigate a shared genetic architecture between smoking and heel estimated bone mineral density (eBMD), a reliable proxy for osteoporosis. We conducted a comprehensive genome-wide cross-trait analysis to identify genetic correlation, pleiotropic loci and causal relationship of smoking with eBMD, leveraging summary statistics of the hitherto largest genome-wide association studies conducted in European ancestry for smoking initiation (Nsmoker = 1 175 108, Nnonsmoker = 1 493 921), heaviness (cigarettes per day, N = 618 489), cessation (Ncurrent smoker = 304 244, Nformer smoker = 843 028), and eBMD (N = 426 824). A significant negative global genetic correlation was found for smoking cessation and eBMD (${r}_g$ = -0.051, P = 0.01), while we failed to identify a significant global genetic correlation of smoking initiation or heaviness with eBMD. Partitioning the whole genome into independent blocks, we observed six significant shared local signals for smoking and eBMD, with 22q13.1 showing the strongest regional genetic correlation. Such a genetic overlap was further supported by 71 pleiotropic loci identified in the cross-trait meta-analysis. Mendelian randomization identified no causal effect of smoking initiation (beta = -0.003 g/cm2, 95%CI = -0.033-0.027) or heaviness (beta = -0.017 g/cm2, 95%CI = -0.072-0.038) on eBMD, but a putative causal effect of genetic predisposition to being a current smoker was associated with a lower eBMD compared to former smokers (beta = -0.100 g/cm2, 95%CI = -0.181- – 0.018). Our study demonstrates a pronounced biological pleiotropy as well as a putative causal link between current smoking status and eBMD, providing novel insights into the primary prevention and modifiable intervention of osteoporosis by advocating individuals to avoid, reduce or quit smoking as early as possible.

PMID:38843381 | DOI:10.1093/jbmr/zjae082

PLoS Genet. 2024 Jun 6;20(6):e1011317. doi: 10.1371/journal.pgen.1011317. Online ahead of print.

ABSTRACT

Evaluation of the apportionment of genetic diversity of human bacterial commensals within and between human populations is an important step in the characterization of their evolutionary potential. Recent studies showed a correlation between the genomic diversity of human commensal strains and that of their host, but the strength of this correlation and of the geographic structure among human populations is a matter of debate. Here, we studied the genomic diversity and evolution of the phylogenetically related oro-nasopharyngeal healthy-carriage Streptococcus mitis and Streptococcus pneumoniae, whose lifestyles range from stricter commensalism to high pathogenic potential. A total of 119 S. mitis genomes showed higher within- and among-host variation than 810 S. pneumoniae genomes in European, East Asian and African populations. Summary statistics of the site-frequency spectrum for synonymous and non-synonymous variation and ABC modelling showed this difference to be due to higher ancestral bacterial population effective size (Ne) in S. mitis, whose genomic variation has been maintained close to mutation-drift equilibrium across (at least many) generations, whereas S. pneumoniae has been expanding from a smaller ancestral bacterial population. Strikingly, both species show limited differentiation among human populations. As genetic differentiation is inversely proportional to the product of effective population size and migration rate (Nem), we argue that large Ne have led to similar differentiation patterns, even if m is very low for S. mitis. We conclude that more diversity within than among human populations and limited population differentiation must be common features of the human microbiome due to large Ne.

PMID:38843312 | DOI:10.1371/journal.pgen.1011317