Mycosis fungoides (MF) is a primary cutaneous lymphoma that in pediatric patients is frequently misdiagnosed as a benign dermatosis. Studies in Mexican children are limited.

To describe the clinical, immunophenotypic, and therapeutic characteristics of MF in a Mexican pediatric series.

It was conducted a cross-sectional study between 2017-2025 at a hospital in Mexico City, which included 17 pediatric patients younger than 18 years of both sexes with a diagnosis of MF.

They were 13 males and 4 females, with a mean age at diagnosis of 11.9 ± 2.8 years and a median disease duration of 3 years; 52.9% of patients were referred with a diagnosis of atopic dermatitis. The most frequent clinical variant was hypopigmented (64.7%). All cases were classified as stage IB. Diagnosis required a median of 2 biopsies, with delays of up to 12 months (range 3-24). All cases showed epidermotropism with CD3 and CD4 positivity (100%), and 88.2% showed CD8 positivity. All patients received topical corticosteroids; 3 received phototherapy, 3 methotrexate, and 3 photopheresis. The classic form of MF was associated with the presence of erythematous patches and erythematous scaly plaques, as well as, in some cases, with the use of methotrexate and phototherapy.

Pediatric MF poses a diagnostic challenge due to its clinical similarity to common dermatoses. Although prognosis is generally favorable, its recurrence requires prolonged follow-up.

Functional status is considered the standard criterion prior to systemic therapy administration; however, in older adults with cancer, this criterion may lead to challenges in this group.

To evaluate the association between suspicion of sarcopenia and systemic treatment toxicity in older adults with cancer.

Prospective cohort study which included 150 older adults with recent diagnosis of cancer, candidates to systemic cancer treatment and who signed informed consent. Older adults with brain metastasis were excluded. Prior to systemic treatment, functional status variables were evaluated: skeletal muscle strength, sarcopenia screening, frailty, and chair stand test. Follow-up evaluations were performed before each systemic treatment cycle. Endpoint was considered as the clinical evidence or laboratory toxicity grade 3 or higher, using the Common Terminology Criteria for Adverse Events, version 5.0, or the completion of the treatment regimen.

The incidence of systemic toxicity was 42.7%. In the comparison between patients without toxicity vs. patients with toxicity, the latter group showed a higher frequency of tobacco use, frailty, risk of sarcopenia, and lower grip strength. Only sarcopenia screening predicted systemic toxicity (hazard ratio [HR]: 2.13, 95% confidence interval [95% CI] 1.16-3.91).

The suspicion of sarcopenia was the only toxicity predictor for systemic therapy in older adults with cancer.

IntroductionPredicting B-Raf proto-oncogene, serine/threonine kinase (BRAF) gene mutations, lateral lymph node metastasis (LLNM) and central lymph node metastasis (CLNM) is crucial for selecting preoperative surgical approaches and predicting survival outcomes in patients with papillary thyroid carcinoma (PTC). In this study, features extracted from ultrasound images were combined with clinical characteristics to construct a nomogram model for predicting BRAF gene mutations, LLNM and CLNM.MethodsIn this retrospective study, 580 patients with pathologically confirmed PTC were enrolled between January 2020 and August 2023 from two medical centers, which was divided into training set, internal validation set and external test set, respectively. Radiomics and deep learning (DL) features were extracted from ultrasound images. Radiomics and DL models were constructed based on the selected features to generate radiomics score (R Score) and DL score (D Score), respectively. Finally, nomogram was developed by integrating R Score, D Score with clinical characteristics to predict BRAF gene mutations, LLNM and CLNM.ResultsIn the study of predicting BRAF mutations, LLNM, and CLNM in PTC, the R model achieved area under curves (AUCs) of 0.70 vs. 0.65 vs. 0.70, 0.77 vs. 0.74 vs. 0.64, and 0.81 vs. 0.74 vs. 0.69 in the training, internal validation and external test sets, respectively. A nomogram achieved AUCs of 0.69 vs. 0.71, 0.75 vs. 0.67 and 0.78 vs. 0.78 in the prediction of BRAF mutations, LLNM, and CLNM for PTC in the internal validation and external test sets, respectively.ConclusionsThis study demonstrates that ultrasound-based model integrating radiomics features, DL features, and clinical factors can effectively predict BRAF mutations, LLNM, and CLNM in patients with PTC. The proposed nomogram models exhibited superior predictive performance compared with radiomics-only and DL-only models.

Tumor tissue is a dynamic system governed by complex transcriptional kinetics. Although scRNA-seq has revolutionized cellular profiling, it captures static expression snapshots, lacking direct access to transcriptional dynamics. Here, we present Kinetics-seq, a time-resolved single-cell method that integrates an in vivo metabolic labeling strategy with scRNA-seq to construct a comprehensive transcriptional kinetic landscape within tissues. This approach enables transcriptome-wide measurement of RNA abundance, turnover, synthesis, and degradation rates at single-cell resolution. By incorporating RNA kinetic parameters, Kinetics-seq introduces a dynamic dimension to cellular profiling, revealing heterogeneities not only across cell types but also within individual populations. Through joint modeling of RNA synthesis and degradation rates, Kinetics-seq uncovers gene-specific regulatory strategies and pronounced kinetic diversity among tumor cells. Moreover, RNA kinetics serves as a screening tool to identify transcriptionally active gene subsets, revealing pathways such as estrogen response early, PI3K-AKT-mTOR signaling, and epithelial-mesenchymal transition that display stronger temporal associations with tumor progression than abundance-based analyses. Collectively, Kinetics-seq provides a powerful tool for refining cellular taxonomy, elucidating RNA regulatory strategies, and identifying actively regulated genes that affect a tumor ecosystem, while also offering opportunities for mechanistic investigation, biomarker discovery, and therapeutic intervention.

Molecular radiotherapy (MRT) for children and young people presents unique challenges distinct from other cancer treatments. It requires specialised inpatient care in paediatric settings, strict radiation safety protocols, and is typically available only at selected centres, making access uneven across regions. Despite the complexity of this treatment, there is a notable lack of research into the holistic needs of parents and caregivers of paediatric patients undergoing MRT. Understanding and addressing these needs could help enhance future care, facilitate earlier interventions, and improve care planning for both patients and their families.

A prospective, systematic assessment of holistic needs was conducted for paediatric and adolescent patients undergoing their first cycle of MRT at a single tertiary referral centre between 2018 and 2022. The evaluation focused on physical, emotional, social, and practical concerns impacting the caregivers.

Fifty patients were included in the study, treated with [¹³¹I]sodium iodide, [¹³¹I]meta-iodobenzylguanidine (mIBG), or [¹⁷⁷Lu]lutetium DOTATATE. The median patient age was 13 years. Thematic analysis identified several key areas of concern: limited access to psychosocial support services, financial burdens due to travel and time off work, and MRT-specific challenges including enforced isolation and separation from family members during treatment.

Holistic needs assessments are vital in identifying and addressing unmet needs in MRT. A coordinated, family-centred, multidisciplinary approach is essential. Future improvements should include enhanced training for healthcare professionals, use of virtual peer support, support for education continuity, and better integration of local resources to support families throughout the treatment journey.

For people living with and beyond cancer, access to clear, accurate, relevant information is crucial for meaningful participation in shared decision-making and is associated with better quality-of-life. Many cancer patients who undergo pelvic radiation experience chronic bowel symptoms, decreasing quality-of-life. We aimed to explore information access among survivors with experience of chronic bowel symptoms and develop a framework to guide future information provision.

We conducted cross-sectional, semi-structured interviews with 28 cancer survivors (14 prostate, 10 gynecological, 4 anal/rectal) with experience of chronic bowel symptoms after pelvic radiotherapy, and 19 health professionals who provide treatment and care for survivors with these symptoms. Participants were recruited through UK cancer charities and National Health Service hospitals. Data were analyzed thematically. Findings informed a framework to guide improvements to information provision, developed with a patient panel.

Data were organized to reflect survivor experiences with information access and provision at different points along their cancer journey: Pre-treatment; Recognizing Symptoms; Managing Symptoms; and two cross-cutting categories of Information Sources and Challenges in Information Provision. The framework encompasses information purpose and channels, survivors' information needs at different time points and challenges and considerations for implementation.

Access to timely, relevant, accurate information was an issue across the cancer pathway for this survivor group. Participants reported disparate information needs which could not have been fully known at treatment outset, and which changed over time. Our framework offers a potential starting point for efforts to improve information access and provision.

To delineate features of hepatic nodules in native liver survivors (NLS) of biliary atresia (BA) post-Kasai portoenterostomy (KPE) and determine the surveillance utility of tumour markers and imaging studies.

This retrospective study conducted in a tertiary referral centre evaluated post-KPE patients who developed liver nodules following operations performed between 1979-2020. These included NLS at time of writing and liver transplant (LT) recipients with evidence of nodules before LT. Demographic, biochemistry, tumour markers, imaging, and histopathological data were collected. Dysplastic and non-dysplastic nodules were compared using Mann-Whitney U and Fisher's exact test.

Among 163 BA patients, of 96 NLS, 17 developed nodules; of 67 post-LT patients, 6 developed nodules before LT. Together, 23 post-KPE patients with nodules were analyzed: 4 dysplastic (one progressed into early hepatocellular carcinoma) and 19 benign lesions. Dysplastic nodules appeared earlier (8.2 vs. 21.2 years, p=0.286) and were larger (11.6 vs. 2.2cm², p=0.284). Alpha-fetoprotein (AFP) levels were similar (2.0ng/mL vs. 3.0ng/mL, p=0.232). All dysplastic nodules exhibited arterial-phase enhancement without portovenous washout on contrast-enhanced computed tomography (CT).

In BA NLS, one-quarter develop hepatic nodules over time; malignant changes are rare, but can occur. Additionally, contrast-enhanced CT surveillance may be useful for larger, or earlier-detected hepatic nodules.

Missed medical appointments, including cancellations and no-shows, disrupt clinical workflows, reduce resource efficiency, and can compromise patient care. This study develops a machine learning (ML) framework to jointly predict cancellations and no-shows using approximately 1.8 million chemotherapy appointments from Dana-Farber Cancer Institute in Boston, Massachusetts, USA. We implement a hierarchical ML approach that first detects cancellations and then predicts no-shows among the remaining cases. Combining static appointment features with dynamic temporal features derived from prior scheduling history, the model achieves F1-scores of 0.80 (cancellations) and 0.75 (no-shows), outperforming single-stage multiclass baselines in identifying the two non-attendance outcomes. To provide actionable insights, our ML pipeline also predicts the underlying reason for a missed visit. Lacking labeled no-show reasons, we apply a semi-supervised learning approach using short-notice cancellations as proxies and achieve F1-scores of 0.60 for cancellation reasons and 0.73 for no-show reasons. Finally, we use both models to conduct a counterfactual analysis to assess whether modifiable scheduling factors - such as appointment timing and provider consistency - can reduce cancellations and missed visits. We find that interventions informed by the literature, such as patient confirmations and scheduling lead time, are less effective in this setting than previously reported. We also evaluate two model-guided operational strategies motivated by the observed prediction patterns. Our findings highlight the value of designing predictive models with prescriptive intent, particularly when the goal is to tailor interventions to the specific operational context of a medical clinic.

Infantile haemangioma (IH) is the most common vascular tumour of infancy. Propranolol is first-line treatment, but response monitoring relies on subjective clinical assessment. Semi-automated photographic erythema quantification may offer a reproducible, low-cost adjunct monitoring tool.

To develop a semi-automated Python-based erythema quantification tool for serial clinical photographs of IH, evaluate its feasibility and intra-rater reliability, and characterise the relationship between colour-based erythema change and clinician-assessed composite response.

Retrospective analysis of a prospective photographic registry at a tertiary paediatric surgery centre. Forty-nine infants with IH treated with propranolol were included. Serial clinical photographs (n = 251) were analysed using a custom Python tool. The erythema index (EI = [R - G] / [R + G + B]), a formula validated for quantification of cutaneous erythema from digital photographs, was calculated from manually selected lesion regions of interest (ROI). Intra-rater reliability was assessed by re-rating 22 photographs from five patients one week apart. Absolute EI change was correlated with prospectively recorded, blinded clinician response scores (0-10).

Of 251 photographs, 242 (96.4%) were analysable (mean 4.9 visits per patient, range 2-11). Intra-rater reliability was high: ICC(A,1) = 0.990(95% CI 0.97-1.00); Bland-Altman mean difference - 0.005 EI units (95% limits of agreement - 0.023 to + 0.013). Mean baseline EI was 0.122 ± 0.058 and mean final EI was 0.115 ± 0.053. Absolute EI change did not correlate with clinician response scores (Pearson r = - 0.084, 95% CI - 0.357 to 0.202, p = 0.566; Spearman r = - 0.087, p = 0.554), consistent across three sensitivity analyses.

Semi-automated erythema quantification from clinical photographs of IH is feasible with high intra-rater reliability. These pilot findings should be interpreted as hypothesis-generating; the study is underpowered for definitive correlation testing, and prospective replication in an adequately powered cohort is required. In this pilot cohort, colour-based EI change alone was insufficient to track the clinician's composite response assessment under real-world uncalibrated photography conditions, consistent with the partial-biomarker nature of colour-only analysis. Prospective studies with standardised photography incorporating colorimetric calibration and composite colour-plus-area scoring are warranted.

Results of patient-reported outcome measurements need to be comprehensible and conclusive for a successful integration into treatment in cancer care. The aim of this study was to determine cut-off values for the recently developed "Hamburg Inventory for Measuring Quality of Life in Oncological Patients-6" (HELP-6), a short measurement for Health-related Quality of Life (HrQoL) in routine care in oncological patients.

Oncological in- and out-patients with differing cancer entities participated in this study. The survey included the HELP-6 and standardized questionnaires (Distress-Thermometer, PHQ-4, Fact-G, PDI-G). Six receiver operating characteristics analyses were performed, one for each scale of the instrument (Emotional Health, Physical Ailment, Social Functionality, Autonomy, Dignity, Resources).

For five of the six scales cut-offs could be determined. Areas under the Curve were between 0.7 and 0.8. However, the Dignity scale demonstrated poor discriminative validity, failing to distinguish adequately between severity levels of patient groups.

By applying the HELP-6 with the cut-off values established in this study, clinicians can more readily interpret patients' HrQoL, thereby supporting effective clinical decision-making. This feature is especially valuable in routine care, where streamlined monitoring of patient quality of life is paramount. Further conceptualization and validation of the Dignity scale, as well as its integration into patient-reported outcome measures, are warranted.

The complete study including the development of the instrument was registered at Open Science Framework ***redacted for peer-review***.

not applicable.