N Z Med J. 2024 Jun 7;137(1596):102-104. doi: 10.26635/6965.6530.
NO ABSTRACT
PMID:38843555 | DOI:10.26635/6965.6530
Category: Nevin Manimala
N Z Med J. 2024 Jun 7;137(1596):35-42. doi: 10.26635/6965.6430.
ABSTRACT
AIMS: New Zealand melanoma incidence rates are amongst the highest in the world. The study aims to provide information on the incidence of cutaneous melanoma in New Zealand from 2000 to 2022.
METHODS: De-identified data were extracted from the New Zealand Cancer Registry using the ICD-10 code for malignant melanoma (C34) and melanoma in situ (MIS) (D03) from 2000 to 2022. Statistical analysis was performed to calculate melanoma incidence rates.
RESULTS: Invasive melanoma (IM) incidence rates demonstrated an increasing trend from 2000 to 2008 (+1.10 per 100,000 person-years per year), followed by an inflection point at 2008 and then a decreasing trend from 2008 to 2022 (-0.28 per 100,000 person-years per year), which was not statistically different from zero/no change. MIS incidence increased from 30.3 to 72.1 per 100,000 person-years between 2000 and 2022.
CONCLUSIONS: The incidence of IM in New Zealand has plateaued in the last decade and was associated with an increase in MIS incidence over the same period. While this trend is encouraging, further research is required to investigate whether there is an actual decline in IM incidence.
PMID:38843548 | DOI:10.26635/6965.6430
J Med Internet Res. 2024 Jun 6;26:e48491. doi: 10.2196/48491.
ABSTRACT
BACKGROUND: Social media has become an increasingly popular and critical tool for users to digest diverse information and express their perceptions and attitudes. While most studies endeavor to delineate the emotional responses of social media users, there is limited research exploring the factors associated with the emergence of emotions, particularly negative ones, during news consumption.
OBJECTIVE: We aim to first depict the web coverage by news organizations on social media and then explore the crucial elements of news coverage that trigger the public’s negative emotions. Our findings can act as a reference for responsible parties and news organizations in times of crisis.
METHODS: We collected 23,705 Facebook posts with 1,019,317 comments from the public pages of representative news organizations in Hong Kong. We used text mining techniques, such as topic models and Bidirectional Encoder Representations from Transformers, to analyze news components and public reactions. Beyond descriptive analysis, we used regression models to shed light on how news coverage on social media is associated with the public’s negative emotional responses.
RESULTS: Our results suggest that occurrences of issues regarding pandemic situations, antipandemic measures, and supportive actions are likely to reduce the public’s negative emotions, while comments on the posts mentioning the central government and the Government of Hong Kong reveal more negativeness. Negative and neutral media tones can alleviate the rage and interact with the subjects and issues in the news to affect users’ negative emotions. Post length is found to have a curvilinear relationship with users’ negative emotions.
CONCLUSIONS: This study sheds light on the impacts of various components of news coverage (issues, subjects, media tone, and length) on social media on the public’s negative emotions (anger, fear, and sadness). Our comprehensive analysis provides a reference framework for efficient crisis communication for similar pandemics at present or in the future. This research, although first extending the analysis between the components of news coverage and negative user emotions to the scenario of social media, echoes previous studies drawn from traditional media and its derivatives, such as web newspapers. Although the era of COVID-19 pandemic gradually brings down the curtain, the commonality of this research and previous studies also contributes to establishing a clearer territory in the field of health crises.
PMID:38843521 | DOI:10.2196/48491
J Clin Oncol. 2024 May 31:JCO2400733. doi: 10.1200/JCO.24.00733. Online ahead of print.
ABSTRACT
PURPOSE: The open-label, phase III EVOKE-01 study evaluated sacituzumab govitecan (SG) versus standard-of-care docetaxel in metastatic non-small cell lung cancer (mNSCLC) with progression on/after platinum-based chemotherapy, anti-PD-(L)1, and targeted treatment for actionable genomic alterations (AGAs). Primary analysis is reported.
METHODS: Patients were randomly assigned 1:1 (stratified by histology, best response to last anti-PD-(L)1-containing regimen, and AGA treatment received or not) to SG (one 10 mg/kg intravenous infusion on days 1 and 8) or docetaxel (one 75 mg/m2 intravenous infusion on day 1) in 21-day cycles. Primary end point was overall survival (OS). Key secondary end points were investigator-assessed progression-free survival (PFS), objective response rate, patient-reported symptom assessment, and safety.
RESULTS: In the intention-to-treat population (SG, n = 299; docetaxel, n = 304), 55.4% had one previous line of therapy. Median follow-up was 12.7 months (range, 6.0-24.0). The primary end point was not met. There was a numerical OS improvement for SG versus docetaxel (median, 11.1 v 9.8 months; hazard ratio [HR], 0.84 [95% CI, 0.68 to 1.04]; one-sided P = .0534), consistent across squamous and nonsquamous histologies. Median PFS was 4.1 versus 3.9 months (HR, 0.92 [95% CI, 0.77 to 1.11]). An OS benefit was observed for SG (n = 192) versus docetaxel (n = 191) in mNSCLC nonresponsive to last anti-PD-(L)1-containing regimen (3.5-month median OS increase; HR, 0.75 [95% CI, 0.58 to 0.97]); this was consistent across histologies. Among patients receiving SG and docetaxel, 6.8% and 14.2% discontinued because of treatment-related adverse events (TRAEs), respectively; 1.4% and 1.0%, respectively, had TRAEs leading to death.
CONCLUSION: Although statistical significance was not met, OS numerically improved with SG versus docetaxel, which was consistent across histologies. Clinically meaningful improvement in OS was noted in mNSCLC nonresponsive to last anti-PD-(L)1-containing regimen. SG was better tolerated than docetaxel and consistent with its known safety profile, with no new safety signals.
PMID:38843511 | DOI:10.1200/JCO.24.00733
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