Durvalumab monotherapy as a consolidation treatment for limited-stage small-cell lung cancer (LS-SCLC) demonstrated a favourable benefit-risk profile in the ADRIATIC study. We evaluated population pharmacokinetics (PopPK) and exposure-response (E-R) relationships of durvalumab in patients with LS-SCLC. The durvalumab PopPK model was updated by integrating PK data from the ADRIATIC study. Individual exposure metrics were derived from empirical Bayes estimates for E-R analyses relating to safety (adverse events [AEs]) and efficacy (progression-free survival [PFS] and overall survival [OS]). A two-compartment model with a time-dependent clearance adequately characterized durvalumab PK data. The typical parameter estimates for baseline clearance, central and peripheral volume of distribution were 0.273 L/day, 3.49 L and 2.35 L, respectively. All identified covariates are considered to have minimal clinical impact on durvalumab PK parameters with effect within 80-125% of typical values. Kaplan Meier plots of PFS or OS stratified by exposure quartiles suggested a plateaued relationship between durvalumab exposure and PFS or OS at the selected dose level of 1500 mg. The Cox PH model analysis did not identify exposure metrics as significant prognostic factors for the OS or PFS hazard. At 1500 mg IV Q4W, a flat E-R relationship was observed between durvalumab PK exposure and safety endpoints including Grade 3 + treatment-related AEs, Grade 3 + treatment-related AEs of special interest, and AEs leading to treatment discontinuation. The results support the use of durvalumab monotherapy for the patients with LS-SCLC, and no dose adjustment is considered necessary based on the PopPK and E-R analyses. NCT03703297.

Diffuse large B-cell lymphoma (DLBCL) and chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) differ markedly in disease biology and treatment intensity, yet comparative renal outcome data are limited. We compared acute kidney injury (AKI) and chronic kidney disease (CKD) incidence between demographically matched DLBCL and CLL/SLL cohorts.

Retrospective cohort study using the TriNetX Global Collaborative Network (143 healthcare organizations; data extracted May 9, 2025). Adults with DLBCL (ICD-10 C83.3) or CLL/SLL (C91.1, C83.0) underwent 1:1 propensity score matching for age, sex, race, and ethnicity. AKI (N17) and CKD (N18) were assessed from day 1 post-index through each patient's available follow-up (an open-ended window; no fixed follow-up duration was generated). Risk differences, risk ratios, and odds ratios (ORs) with 95% CIs were calculated using two-proportion z-tests.

After matching, 19,438 patients (9719/cohort) were analyzed. AKI occurred in 22.9% of DLBCL versus 20.9% of CLL/SLL patients (risk difference 2.0%, 95% CI 0.8-3.1%; risk ratio 1.094, 95% CI 1.037-1.154; OR 1.122, 95% CI 1.048-1.201, p = 0.001). CKD occurred in 18.8% of DLBCL versus 22.7% of CLL/SLL patients (risk difference -4.0%, 95% CI -5.1 to -2.8%; risk ratio 0.825, 95% CI 0.781-0.872; OR 0.785, 95% CI 0.732-0.842, p < 0.001). Demographic characteristics were well balanced (SMD 0.001-0.038). Comorbidities and follow-up duration were not captured by this matching algorithm and are addressed as limitations.

DLBCL showed modestly higher AKI risk and CLL/SLL showed modestly higher CKD burden in this demographically matched cohort. Because comorbidities were not matched and absolute differences were small, these findings are hypothesis-generating, supporting attention to renal monitoring in both subtypes pending comorbidity-adjusted, prospective confirmation.

This study sought to compare the effectiveness of cognitive behavioral stress management (CBSM) and acceptance and commitment therapy (ACT) on the quality of life and fatigue of caregivers of cancer patients.

This single-site, parallel-group, three-arm, superiority randomized controlled trial with a 1:1:1 allocation ratio includes 66 caregivers of cancer patients who were randomly assigned to either the CBSM, ACT, or control group. The CBSM and ACT interventions each consisted of eight in-person sessions, conducted twice a week for 90 min each. Participants in all three groups completed the Caregiver Quality of Life Index-Cancer and the Multidimensional Fatigue Inventory in all pre, post, and follow-up phases.

A significant difference was observed in the quality of life and caregiver fatigue among the three groups in both the posttest and follow-up phases (p < 0.05), which were maintained 2 months after the intervention, apart from quality of life in the CBSM group. However, there was no statistically significant difference in the variables between the two interventions (p > 0.05).

The effectiveness of both ACT and CBSM in enhancing caregivers' quality of life and alleviating fatigue offers a promising perspective for the development and implementation of supportive and therapeutic programs aimed at enhancing the mental health of caregivers of cancer patients.

www.

gov , NCT07329868 (December 29, 2025, retrospectively registered).

Participation in breast cancer screening among culturally diverse women in Australia remains below national targets. Healthcare providers, particularly general practitioners (GPs), play a pivotal role in bridging communication and knowledge gaps and in advocacy, especially for under-screened South Asian (Pakistani and Indian) women.

To explore communication and health education strategies used by healthcare providers to encourage breast cancer screening among culturally diverse South Asian women living in Victoria.

A qualitative study involving semi-structured interviews with 15 GPs and non-primary healthcare providers in Victoria, Australia. Participants were recruited using purposive and snowball sampling methods, drawing from primary care, specialist networks and peer-to-peer referrals. Reflexive thematic analysis was applied to identify communication strategies and system-level insights.

Three major themes were identified: (1) encouraging health engagement; (2) communication strategies; (3) cultural sensitivity of healthcare providers. Trust-building strategies were important in encouraging health engagement and reducing resistance to screening and misconceptions. Participants reported low levels of health literacy, including limited awareness of BreastScreen Victoria's free service. While interpreters aided communication, they also posed challenges in maintaining efficient consultations. Healthcare providers promoted patient-centred, visual resources to support screening discussions. Cultural sensitivity was emphasised through the use of culturally competent tools and healthcare providers' ongoing cultural training. Existing screening informational resources were considered insufficient to address the cultural preferences of screening South Asian women.

Strengthening breast cancer screening for culturally diverse women relies on building trust through culturally competent healthcare providers who can support their patients' engagement with screening through empowering communication, tailored tools and shared decision-making.

Healthcare providers are key enablers of breast cancer screening participation among South Asian women. Investing in culturally competent communication, tailored resources and workforce training could substantially improve screening engagement among South Asian women who remain under-screened despite access to free screening services.

While computed tomography (CT) remains an important imaging modality in radiotherapy planning, magnetic resonance imaging (MRI)-only workflow, often realized via the generation of synthetic computed tomography (sCT), is desired due to superior soft-tissue contrast and less susceptibility to registration errors.

The aim of this study was to investigate the feasibility of applying sCT, generated from MRI using a deep learning model, to pelvic radiotherapy planning. By comparing differences between conventional CT and sCT in terms of image quality, dosimetric parameters, and three-dimensional (3D) dose distributions, the clinical potential of an MRI-only radiotherapy workflow was evaluated.

Fifteen patients who underwent both pelvic CT and MRI examinations were retrospectively enrolled. For the same patients, sCT images were generated from the MRI using a pretrained pelvic deep learning model integrated in the syngo.via VB60A software platform. Treatment plans originally created on planning CT (pCT) images were re-calculated on corresponding sCT datasets. Subsequently, the mean absolute error (MAE) of CT numbers, Dice similarity coefficients (DSCs) for major structures, dose-volume histogram (DVH) parameters for the planning target volume (PTV) and major organs at risk (OARs), and 3D dose distributions were compared between plans calculated on pCT and sCT.

In terms of image quality, sCT demonstrated comparable CT number accuracy with pCT for soft tissue structures, with MAEs ranging from 6.8 to 8.5 Hounsfield units (HU) for the PTV, bladder, and rectum. Higher MAEs were observed for bony structures (femoral heads and bone marrow), with average MAEs ranging between 17 and 19 HU. The DSC was 0.94 ± 0.01 for the right femoral head, 0.93 ± 0.01 for the left femoral head, and 0.85 ± 0.03 for bone marrow. Regarding dosimetric comparison, the mean absolute differences in key dosimetric parameters for the PTV (D98%, D95%, and Dmean) were all below 0.6%, remaining within clinically acceptable limits. Among the OARs, except for relatively large differences for the maximum and minimum doses in the bladder, the mean dose (Dmean) differences for the rectum, femoral heads, and bone marrow were minimal (mean absolute value ≤ 0.34%), indicating high reliability. Analysis of 3D dose distributions using a 2% 2 mm γ criterion revealed an average γ passing rate of 95.92% between sCT and pCT, satisfying routine clinical quality assurance requirements.

The findings of our study demonstrate the feasibility of applying sCT generated from MRI using a deep learning model to pelvic radiotherapy planning. The MRI-only workflow proposed on this basis eliminates systematic errors introduced by CT-MRI image registration, optimizes the clinical workflow, and fully exploits the superior soft-tissue contrast of MRI to improve target delineation accuracy. The proposed approach provides a novel technical paradigm for achieving more precise and efficient individualized radiotherapy.

Fertility loss related to cancer treatment can significantly affect quality of life among pediatric, adolescent, and young adult patients. Many regional cancer centers lack an in-house reproductive medicine unit, which creates barriers to timely fertility preservation (FP). To address this gap, our hospital established a multidisciplinary Oncofertility Working Group in collaboration with nearby reproductive centers. This study evaluated referral activities and outcomes after working group establishment and aimed to propose a feasible FP support implementation model for cancer centers without reproductive medicine units.

We developed a standardized referral pathway and consultation checklist sheet in collaboration with a primary external reproductive center. We retrospectively analyzed consecutive patients referred for FP using consultation checklist sheets and medical records. Questionnaire surveys were conducted at working group launch and 4 years later to assess institutional changes.

Between April 2022 and September 2025, 45 patients (24 female and 21 male) were referred for FP. The median interval from referral to reproductive consultation was 2 days. FP was performed in 70.8% of female patients and 95.2% of male patients. Survey results showed a shift from department-dependent practices to a standardized referral system.

Even in a regional cancer treatment cooperation base hospital without an in-house reproductive medicine unit, multidisciplinary coordination and structured external collaboration can deliver timely and practical FP support. This implementation model may help reduce regional disparities in oncofertility care, although further work should strengthen information sharing and long-term follow-up.

Accurate CT/MR registration is important in stereotactic brain radiotherapy, where small spatial errors may affect target localization and treatment planning. In many clinical settings, registration quality is still assessed primarily through manual visual inspection. However, time and workflow constraints may limit the consistency and depth of manual evaluation.

This study aimed to develop a 3D convolutional neural network (3D CNN)-based quality assurance (QA) method for rigid brain CT/MR registration using paired sub-volumes and a registration-level mean probability score (μ). The proposed method classifies local CT/MR registration quality, while the final registration-level assessment is based on μ across the sampled sub-volumes.

The study included 209 patients. Of these, 202 comprised the primary cohort and were divided patient-wise into 128 training, 33 validation, and 41 test patients. For each patient, 25 skull-based CT/MR sub-volumes of 42 ×  42 ×  42 voxels were used as a two-channel CNN input. High-quality examples were obtained from clinically approved registrations, while low-quality examples were generated using rigid perturbations of the complete MR volume. The mean predicted probability across the 25 sub-volumes was used as the registration-level score μ, and the validation-derived threshold of 0.5871 was fixed for testing. Seven additional patients, separate from the 202-patient cohort, were evaluated after model development and threshold selection were completed using registrations before and after physician correction.

On the held-out test set, patch-level accuracy was 85.90%, with an ROC AUC of 0.929 and average precision of 0.920. At the registration level, accuracy was 97.56% and ROC AUC was 0.999. All 41 low-quality registrations were correctly flagged, while 39 of 41 high-quality registrations were correctly accepted. In the additional clinical evaluation, all seven initial registrations requiring correction were classified as low quality, while six of seven corrected registrations were classified as high quality, resulting in an overall accuracy of 92.86%.

The proposed method combined local CNN predictions into a registration-level μ score and showed strong performance on held-out and clinical cases. It may provide a quantitative screening measure for rigid brain CT/MR registration QA while maintaining clinical review as the final decision step.

End-to-end AI-based automated contouring and radiotherapy planning systems promise substantial gains in efficiency and consistency but also introduce new safety risks, including user input errors that occur early in the workflow. This study evaluates the ability of standard physics plan review to detect user errors in prescription and planning target volume (PTV) margin entry in a fully automated planning workflow.

A prototype of the Radiation Planning Assistant (RPA) was used to generate fully automated prostate cancer treatment plans for 20 patients. Five cases intentionally included incorrect prescriptions or non-standard PTV margins. Five clinical medical physicists independently performed physics plan reviews in a commercial treatment planning system, assuming a standard clinical workflow and without access to user guides or service request forms. Reviews were conducted in two phases, with and without margin information embedded in structure names. A third phase evaluated whether adding reference expansion structures improved margin error detection.

Incorrect prescriptions were detected in 80% of cases, with no false-positive identification of correct prescriptions. In contrast, detection of incorrect PTV margins was highly inconsistent. Two physicists did not evaluate margins and missed all margin errors. Three physicists identified all intentional margin errors but demonstrated poor specificity, frequently flagging correct cases as incorrect (specificity range: 13%-63%). Including margin information in structure names and adding reference expansion structures did not improve specificity or overall detection performance.

Physics plan review was unreliable for detecting incorrect PTV margins in a fully automated planning workflow, even when additional cues were provided. Although based on a limited dataset, these findings indicate that traditional plan review processes alone are insufficient to mitigate this failure mode. Alternative risk-reduction strategies-such as timely workflow-embedded alerts, targeted checklists, automated verification tools, and careful expectation setting-are likely required to improve safety in AI-driven radiotherapy planning systems.

CD19-targeting chimeric antigen receptor T-cells (CAR-T) and blinatumomab represent two leading immunotherapies for relapsed/refractory B cell acute lymphoblastic leukemia (r/r B-ALL). Despite sharing the same target, their differential clinical efficacy and underlying mechanisms remain unclear.

This retrospective study enrolled 106 r/r B-ALL patients (61 CD19 CAR-T vs 45 blinatumomab) between February 2020 and August 2023. The complete response (CR) rate, long-term survival, and therapeutic toxicities were compared between the two cohorts. Additionally, we conducted scRNA-seq on nine samples of patient-derived CAR-T/ blinatumomab-elicited T cells after infusion and performed a head-to-head comparison in vitro.

Overall, the CR or CR with incomplete count recovery (CR/CRi) rate by day 28 after infusion was 96.6% (56/58) in the CAR-T cohort and 77.8% (35/45) in the blinatumomab cohort (p=0.008). With a median follow-up of 10 months (IQR 5.0-19.4), overall survival (OS) and leukemia-free survival (LFS) were comparable. In patients with higher tumor burden (minimal residual disease >20%), CAR-T was associated with a longer LFS (HR 0.453, 95% CI 0.226 to 0.908, p=0.026) compared with blinatumomab. In patients with relapsed disease, CAR-T showed prolonged LFS (HR 0.415, 95% CI 0.221 to 0.778, p=0.006) and a trend toward improved OS (p=0.088). All toxicities were reversible, and any adverse events (AEs) were similar (98.4% vs 88.9%), but severe AEs (grade ≥3) were higher with CAR-T, especially cytokine release syndrome (42.6% vs 13.3%, p<0.001). In addition, scRNA-seq data provided correlative evidence of functional enrichment of effector cells in CAR-T samples during peak expansion at 2 weeks post infusion. Head-to-head comparison in vitro is consistent with the possibility that CAR-T cells may sustain effector function and cytotoxicity following tumor engagement, whereas blinatumomab-elicited T cells tended to show relatively higher exhaustion and reduced cell recovery.

Our findings suggest that CD19 CAR-T therapy is associated with a higher CR/CRi rate compared with blinatumomab, particularly in patients with high tumor burden and relapsed disease, despite a higher severe toxicity profile.

This study aimed to assess the knowledge, attitudes, and practice behaviors of oncology physicians and nurses regarding advanced care planning (ACP) for patients with cancer and to identify barriers to ACP in Oman.

From July 2022 to February 2023, we conducted a multi-center descriptive cross-sectional study in three tertiary cancer care referral hospitals in Oman. The sample comprised 296 oncology physicians (28.7 %) and nurses (71.3 %). Data were collected using the Knowledge, Attitudes, and Practice Behaviors for Advance Care Planning Scale.

Most participants had inadequate knowledge (91.9 %), practice behaviors (48.0 %), and attitudes toward ACP (46.0 %). Physicians had higher knowledge (9.07 ± 2.09 vs. 7.87 ± 2.91) and attitude (81.86 ± 11.01 vs. 70.89 ± 10.28) scores than nurses (P < 0.01). There was no significant difference between physicians' and nurses' practice behaviors (P = 0.077). The other barriers to implementing ACP were lack of communication skills in handling ACP (57.6 %), lack of organizational policies (45.1 %), patients (38.7 %), and their family's lack of readiness and willingness to discuss ACP.

Nurses' and physicians' inadequate knowledge and practices are the main barriers impacting ACP for patients with cancer in Oman. Educational interventions and streamlined clinical policies are needed to improve ACP implementation in Oman.