Accurate disease prognosis is essential for patient care but is often hindered by the scarcity of longitudinal data. This study explores deep learning training strategies that utilize large, accessible diagnostic datasets to pretrain models aimed at predicting future disease progression in knee osteoarthritis (OA), Alzheimer's disease (AD), and breast cancer (BC). While diagnostic pretraining improves prognostic task performance, naive fine-tuning for prognosis can cause 'catastrophic forgetting,' where the model's original diagnostic accuracy degrades, a significant patient safety concern in real-world settings. To address this, we propose a sequential learning strategy with experience replay. We used cohorts with knee radiographs, brain MRIs, and digital mammograms to predict 4-year structural worsening in OA, 2-year cognitive decline in AD, and 5-year cancer diagnosis in BC. Our results showed that diagnostic pretraining on larger datasets improved prognosis model performance compared to standard baselines, boosting both the Area Under the Receiver Operating Characteristic curve (AUROC) (e.g., Knee OA external: 0.770 vs 0.747; Breast Cancer: 0.874 vs 0.848) and the Area Under the Precision-Recall Curve (AUPRC) (e.g., Alzheimer's Disease: 0.752 vs 0.683). Additionally, a sequential learning approach with experience replay achieved prognostic performance comparable to dedicated single-task models (e.g., Breast Cancer AUROC 0.876 vs 0.874) while also preserving diagnostic ability. This method maintained high diagnostic accuracy (e.g., Breast Cancer Balanced Accuracy 50.4% vs 50.9% for a dedicated diagnostic model), unlike simpler multitask methods prone to catastrophic forgetting (e.g., 37.7%). Our findings show that leveraging large diagnostic datasets is a reliable and data-efficient way to enhance prognostic models while maintaining essential diagnostic skills.

Vaccination against the human papillomavirus (HPV) is an effective way to avert cervical cancer. However, acceptance in Morocco remains inadequate. The aim of this study was to measure the prevalence of parental HPV vaccine refusal and the risk factors associated with it.

Between 3 March and 30 September 2025, a multicenter cross-sectional survey was conducted among Moroccan parents of girls aged 11-14 who attended health facilities. The study looked at sociodemographic factors, knowledge regarding HPV and cervical cancer, and vaccination attitudes. A multivariate logistic regression analysis was used to identify risk factors for vaccination refusal.

The research included 1,444 participants with an average age of 37.7 ± 6.6 years. Of them, 415 refused HPV vaccination for their daughters, resulting in a prevalence of 28.7%. Vaccine refusal was substantially related to higher educational levels, lower income, less faith in the healthcare system, less knowledge about cervical cancer and its symptoms, and insufficient information regarding the HPV vaccine as seen by the media. Refusal was also associated with a poor perception of the seriousness of HPV infection, fear of vaccinating daughters, noncompliance with past vaccination schedules, difficulties accessing health centers, and a lack of recommendations from healthcare professionals. In contrast, refusal was inversely associated with parents who were uninformed of the proper number of vaccination doses or uninformed regarding the availability of the HPV vaccine at health centers or who feared the vaccine may cause an adverse reaction.

Parental refusal of HPV vaccination is still a substantial obstacle. To increase acceptability and enhance cervical cancer prevention in Morocco, it is critical to expand communication strategy, boost public knowledge, and assure active participation of healthcare professionals.

Breast cancer is the most prevalent cancer and the leading cause of cancer-related deaths among Jordanian women. Breast self-examination (BSE) plays a vital role in the early detection of breast cancer, improving survival rates. Despite its proven benefits, BSE remains underutilized in Jordan. This study aimed to explore the factors influencing BSE practices among married Jordanian women aged 20-49 years, utilizing data from the Jordan Population and Family Health Survey (JPFHS).

The study analyzed data from the 2023 JPFHS, encompassing a representative sample of 12,595 Jordanian women aged 15-49. The study examined various socioeconomic, demographic, behavioral, and geographic variables. Socioeconomic and demographic factors included age, education level, wealth index, employment status, marital status, parity, and current pregnancy status. Behavioral factors encompassed smoking frequency and media consumption habits, such as internet use, the frequency of watching television, listening to the radio, and reading newspapers or magazines. Geographic variables included the type of residence (urban or rural) and the governorates where participants lived. Associations between these variables and BSE were assessed using multivariable logistic regression.

Among the 12,304 married women included in the analysis, 9,851 women reported not performing BSE, while 2,453 women indicated that they had. Multivariate analysis revealed that significantly better BSE practice was observed among older women (e.g., age 45-49 vs 20-24: AOR 3.08, p < 0.001), those with higher education levels (e.g., secondary vs no education: AOR 2.41, p = 0.027), and wealthier women (e.g., richest vs poorest: AOR 1.54, p = 0.023). Additionally, multiparous women, daily smokers, and women with frequent internet use and frequent reading of newspapers or magazines were also more likely to practice BSE. Regional differences showed that women in Ajloun, Aqaba, and Balqa were more likely to perform BSE, while women in Irbid and Mafraq had lower rates of BSE practice.

To improve BSE rates among married women in Jordan, targeted health campaigns should focus on younger, less educated, and economically disadvantaged women, particularly in Irbid and Mafraq. Culturally sensitive education, digital platforms, and community outreach can raise awareness and address barriers like stigma and misconceptions, promoting proactive breast health practices nationwide. Future researchers are encouraged to further investigate cultural barriers toward BSE.

The Ki-67 proliferation index is a critical prognostic marker in pancreatic ductal adenocarcinoma (PDAC); however, its assessment relies on invasive tissue sampling. Ki-67 expression reflects active tumor cell proliferation and is associated with aggressive tumor behavior. A preoperative, noninvasive method to predict Ki-67 status would therefore be valuable for clinical decision-making. Dual-energy CT (DECT) can provide quantitative parameters related to tumor vascularity and composition, potentially reflecting proliferative activity. Additionally, clinical biomarkers such as CA125 may offer complementary information regarding tumor biology. Therefore, the development of a reliable noninvasive approach to preoperatively determine Ki-67 status is of considerable clinical importance.

To develop and validate a noninvasive approach for predicting Ki-67 expression in pancreatic ductal adenocarcinoma by integrating quantitative dual-energy CT parameters and clinical biomarkers.

This retrospective study included 148 PDAC patients randomly divided into training (n = 89) and validation (n = 59) sets (6:4 ratio). All patients underwent preoperative DECT scans, and quantitative parameters including normalized iodine concentration (NIC), effective atomic number (Zeff), spectral attenuation slope (λ), etc. were obtained from three contrast phases. Serum tumor markers (CA19-9, CA125, CA50, CEA) and clinical features were analyzed. Multivariate logistic regression was used to identify predictors of Ki-67 expression. A nomogram and 3-D probability surface were developed to intuitively demonstrate the model's predictive structure and decision-making process. Model performance was validated using ROC analysis, calibration curves, and decision curve analysis. Innovatively, kernel-density ridgeline plots and prediction-error bar plots were employed to comprehensively evaluate risk distribution and prediction accuracy, demonstrating the model's stability.

The joint model demonstrated excellent predictive performance, achieving AUCs of 0.803 in the training set and 0.810 in the validation set, outperforming both the clinical-only model (training AUC = 0.682, validation AUC = 0.751) and the DECT-only model (training AUC = 0.712, validation AUC = 0.702). Multivariate analysis identified arterial-phase normalized iodine concentration (A-NIC) (p = 0.046) and CA125 (p = 0.005) as independent predictors of Ki-67 expression. These two parameters formed the basis of the final predictive model, demonstrating consistent diagnostic value across both cohorts.

Integration of DECT parameters and clinical biomarkers allows accurate noninvasive prediction of Ki-67 expression in PDAC, offering a potential tool for preoperative assessment of tumor proliferation.

FilmQADose is an open-source, Python-based software for radiochromic film dosimetry, designed to provide medical physicists with a freely available, extensible tool for two-dimensional dose verification in radiotherapy. It covers the full film QA workflow, from calibration curve generation to plan-to-film comparison, targeting clinical and research centers that require an accessible alternative to commercial solutions.

The software was developed in Python using open-source scientific libraries for image processing, curve fitting, DICOM handling, and gamma analysis. Core functionalities include rational and polynomial calibration models, multichannel dose reconstruction, normalized cross-correlation template matching for automatic alignment, and gamma analysis. Validation was performed using irradiated Gafchromic EBT3 films in square field, pyramidal, and breast IMRT plans. Measured dose maps were compared against treatment planning system calculations using 3%/3 mm gamma criteria.

FilmQADose processes TIFF images acquired from flatbed scanners and DICOM RT Dose files exported from treatment planning systems. Output dose maps are generated in DICOM 2D format. The software is implemented in Python with standard scientific Python dependencies and includes a graphical user interface built using PySide6. The source code, documentation, and usage guides are publicly available at: eduardoh27.github.io/FilmQADose.

The software supports clinical quality assurance in IMRT dose verification, as well as for research applications in radiochromic film dosimetry methodology. A limitation is the absence of lateral response artifact correction and recent machine-learning-based calibration methods.

Two decades ago, two papers in Nature described how PARP inhibitors selectively killed cells deficient in the BRCA1 or BRCA2 tumour suppressor genes, observations that led to the first clinically approved treatment of a cancer with a targeted therapy selected based on a germline biomarker. This work was recognized by Nature as one of the top 20 discoveries in cancer in the twenty-first century and provides a compelling example of leveraging fundamental biology discovery for patient benefit. For people with specific forms of breast, ovarian, prostate or pancreatic cancer, these discoveries changed their care, enabling the use of more effective and better tolerated targeted therapies that both improve survival and quality of life. This in turn extended the role of germline BRCA1 and BRCA2 mutation testing from determining risk in the unaffected, to being a companion diagnostic biomarker used to determine therapy for a patient with cancer. The significance of these discoveries spread beyond BRCA1-mutant and BRCA2-mutant cancers: the synthetic lethal concept of the BRCA-PARP inhibitor effect highlighted the myriad levels of functional redundancy that exist in tumour cells and stimulated the search for other tumour-specific synthetic lethal effects that could be exploited therapeutically. Here we distill the learnings from the past two decades in this field.

Our previous findings demonstrated the promising antitumor activity and manageable safety of sintilimab-lenvatinib conversion therapy. The current study aimed to evaluate long-term survival outcomes in patients with unresectable hepatocellular carcinoma (HCC) who underwent sequential surgical resection after successful conversion therapy. In this prospective, single-arm, expansion, phase II trial, patients with unresectable HCC received lenvatinib plus sintilimab conversion therapy. Hepatectomy was performed in consenting patients after successful conversion therapy. The primary endpoint was the conversion rate; secondary endpoints included median overall survival (OS), 5-year survival rates, and recurrence-free survival (RFS). Successful conversion was achieved in 67 of 120 patients (56%, 67/120). Independent imaging review per mRECIST and RECIST v1.1 criteria demonstrated objective response rates of 58.3% (70/120) and 45.8% (55/120), respectively. With a median follow-up of 41.0 months (95% confidence interval [CI], 39.5-42.5) for the entire cohort, the median OS was 36.0 months (95% CI, 25.0 to not estimable [NE]), with a 5-year OS rate of 42.6% (95% CI, 34.0-53.0). Following multidisciplinary team evaluation and consideration of patient preferences, 60 patients underwent surgical resection, achieving a median RFS of 40.0 months (95% CI, 24.0 to NE) and a 5-year survival rate of 73.9% (95% CI, 62.7-87.1). Grade ≥3 treatment-related adverse events occurred in 37 patients (31%). Approximately half of the patients with unresectable HCC achieved successful conversion after sintilimab plus lenvatinib therapy. Among those who achieved successful conversion, subsequent curative surgery demonstrated not only a favorable safety profile but also significant survival benefits. Trial registration number: ChiCTR1900023914.

The optimal strategy for combining radiotherapy (RT) and immunotherapy remains under intensive investigation. Here we developed TRIDENT (Triple Radio-Immunotherapy-Driven ENhanced Therapy), a novel triple-modality regimen combining immunomodulatory low-dose RT (LDRT) to large tumor(s), immunogenic high-dose RT (HDRT) to small tumor(s), and PD-1 blockade. In our phase I trial of 29 patients with treatment-naïve, PD-L1-positive advanced non-small cell lung cancer (NSCLC), TRIDENT achieved a median overall survival (mOS) of 51.3 months (95% CI, 20.7-not reached), higher than outcomes typically reported with contemporary standard (chemo)immunotherapy. This durable survival signal was corroborated in an independent real-world cohort of 97 patients with advanced lung cancer (mOS: 41.5 months; 95% CI, 26.3-63.7). Mechanistically, TRIDENT elicited neutrophil-dependent, systemic antitumor immunity and induced a distinct population of antitumor TNF-α⁺ neutrophils marked by increased MHC and costimulatory molecule expression. Neutrophil recruitment was driven by the CXCL-CXCR2 axis, and polarization toward an antitumor state was programmed by treatment-induced IFN-γ and GM-CSF. TNF-α⁺ neutrophils enhanced CD8⁺ T-cell function via ICAM-1-LFA-1 interactions, and adoptive transfer confirmed their intrinsic antitumor activity in vivo. Spatial transcriptomics of patient tumor tissues further identified a TNF-α⁺ neutrophil-effector CD8⁺ T-cell niche after TRIDENT, providing a stimulatory signal to effector CD8⁺ T cells. In line with these mechanistic findings, clinical biomarker analyses linked neutrophil number with prolonged survival. TRIDENT activates an RT-driven neutrophil-CD8⁺ T-cell axis and promotes survival-associated neutrophil activation. These mechanistic insights, coupled with durable survival in our phase I trial, position TRIDENT as a promising strategy for metastatic NSCLC currently undergoing randomized phase II evaluation. Our study also highlights TNF-α⁺ neutrophils as a promising therapeutic strategy to enhance antitumor efficacy.

A 40-year-old man with acquired immunodeficiency syndrome (AIDS) presented with severe thrombocytopenia and disseminated Kaposi's sarcoma (KS). Initially diagnosed with immune thrombocytopenic purpura (ITP), he was treated with corticosteroids and antiretroviral therapy; however, his condition worsened. He met the criteria for Kaposi's sarcoma-associated inflammatory cytokine syndrome (KICS) and received liposomal doxorubicin, showing temporary improvement. KS progression was observed after immune recovery, suggesting KS-associated immune reconstitution inflammatory syndrome. Rituximab was administered, but the patient deteriorated and died. This case highlights the difficulty in distinguishing KICS from ITP, and the importance of an early diagnosis and multidisciplinary care in advanced AIDS.

Pembrolizumab is an immune checkpoint inhibitor that has been widely used in cancer treatment, and its approved indications have expanded rapidly in recent years. However, the effects of this increase on immune-related adverse events (irAEs) remain unclear. Using data from the Japanese Adverse Drug Event Report (JADER) database and the National Database of Health Insurance Claims and Specific Health Checkups (NDB Open Data), we analyzed trends in the number and characteristics of spontaneously reported adverse events associated with pembrolizumab from fiscal years 2016 to 2024. The number of adverse event reports in JADER generally increased in parallel with prescription volume. Following the expansion of indications for gynecological cancers (such as breast, uterus, and cervix cancers) around 2021, a marked increase in reports was observed from 2022. During this period, the demographic profile of reported patients shifted from predominantly older males to middle-aged females. Regarding cancer types, the proportion of reports on breast and uterus cancers increased significantly, whereas those on lung cancer declined. In addition to pulmonary disorders, endocrine disorders became increasingly reported and represented the most frequent category in fiscal year 2022. The distribution of irAEs by cancer type suggested potential associations; pulmonary toxicity was more frequent in lung cancer, whereas endocrine toxicity was predominant in breast, uterus, and cervix cancers. Our findings indicate that the expansion of pembrolizumab indications has substantially altered the profile of reported immune-related adverse events in Japan, highlighting the need for ongoing pharmacovigilance tailored to cancer type and patient demographics.