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PubMed2026

Robust optimisation for photon radiotherapy: A scoping review of models, paradigms, and reporting.

BACKGROUND AND PURPOSE: Robust optimisation offers an alternative to conventional margin-based photon radiotherapy planning by explicitly modelling uncertainty, but practice is variable and not standardised. MATERIALS AND METHODS: A scoping review was conducted to map robust optimisation for photon external beam radiotherapy. Electronic searches of Scopus, PubMed and Google Scholar (2000-2025, English language) identified planning studies that incorporated modelled uncertainties into the optimisation process and reported at least one robustness-related outcome. Data were charted on clinical context, uncertainty models, optimisation paradigms, robustness metrics and evidence for clinical implementation. RESULTS: Seventy-one studies were included. Most investigated prostate, breast or lung cancer and used intensity-modulated radiotherapy or volumetric-modulated arc therapy in commercial or research treatment planning systems. Scenario-based worst-case (minimax) optimisation was the dominant paradigm in clinically oriented work, while chance-constrained, conditional value at-risk, distributionally robust and adaptive formulations were confined to small methodological series. Uncertainty modelling focused mainly on rigid set-up error; fewer studies incorporated respiratory motion, inter-fraction anatomical change, dose-calculation uncertainty or biological variation. Robustness was evaluated with diverse scenario-based dose-volume metrics, probabilistic coverage measures, composite robustness indices and, less often, biological endpoints. Direct clinical implementation reports were scarce. CONCLUSION: Robust photon planning is technically feasible and generally maintains or improves target coverage and organ sparing compared with margin-based planning. However, heterogeneity in uncertainty models, optimisation configuration and robustness reporting limits comparison and synthesis. Pragmatic minimum standards are proposed to support future consensus and wider clinical adoption.

Humans↗

PubMed2026

Time to subsequent therapy (TTST) as an endpoint in clinical studies: development of standardized documentation of subsequent therapy through systematic literature review, expert interviews, and Delphi survey.

BACKGROUND: The endpoint Time to Subsequent Therapy (TTST) is an intermediate endpoint used in research and regulatory assessments. TTST denotes initiation of subsequent therapy and is a clearly definable, clinically relevant event for healthcare professionals. However, it has not been systematically established to which extent TTST is subjectively meaningful to patients. The objective of this study was to define TTST as a patient-relevant intermediate endpoint. METHODS: The study examined five oncological indications (breast cancer, prostate cancer, melanoma, multiple myeloma, and non-small cell lung cancer) using a systematic literature review, analysis of case report forms used in international randomized controlled trials, review of German Federal Joint Committee (G-BA) documents, semi-structured interviews and a two-stage Delphi survey with healthcare professionals, patients, and relatives. RESULTS: A total of 35 individuals participated in qualitative interviews. Most of them rated TTST as particularly significant. The Delphi Survey included 264 interviewees in round one, and 117 in round two. Patient-relevance of TTST was confirmed by 81% of respondents (95% confidence interval 76%, 85%). Nine treatment scenarios that justify TTST were identified. To capture patient-relevance, prospective collection of reasons for and consequences of therapy change are required. A checklist with standardized response formats plus free-text fields was developed: a comprehensive master checklist for flexible, complete documentation and a short version focused on therapy change-specific items. CONCLUSIONS: TTST is an intermediate endpoint whose systematic documentation of characteristics demonstrating patient-relevance can be standardized in research and clinical practice using the developed checklists.

Humans↗

PubMed2026

Complementary feeding patterns in preterm and term infants.

Complementary feeding is essential for infants' nutritional status and development, marking the transition to solid foods when breast milk or formula alone is insufficient. Despite its importance, clear recommendations on which foods to introduce when initiating complementary feeding in preterm infants are lacking. By using data from our previously published randomized controlled trial on the timing of complementary feeding in preterm infants, the current study explores the complementary feeding patterns of preterm infants and compares them with those of term-born infants, providing insights into parental decision-making and potential long-term health impacts. Complementary feeding practices differed significantly between preterm (n = 255) and term (n = 159) infants, with preterm infants more often receiving vegetables as their first solid food (85.4% versus 68.8%, difference 17.6% with 95% CI 12-35%). The group with early introduction of vegetables had a lower BMI-for-age z-scores (β -0.28 [95% CI -0.55 - 0.02]) and weight-for-height z-scores (β -0.27 [95% CI -0.53 to -0.01]) at two years of age. Additionally, preterm infants showed a greater variety in the numbers of different fruits and vegetables consumed by six months (corrected) age than term-born counterparts (8.29 (SD 3.65) versus 6.26 (SD 3.47), p < 0.001). These results indicate that complementary feeding patterns in preterm infants differ from term-born infants, with potential positive implications on growth. These data contribute to the development of accurate feeding protocols for preterm infants. Given that feeding practices are culturally influenced, further multinational research is essential to refine complementary feeding guidelines for preterm infants and support caregivers in informed decision-making.

Humans↗

PubMed2026

Cancer statistics for Asian American, Native Hawaiian, and Pacific Islander people, 2026.

BACKGROUND: Cancer statistics for Asian American and Native Hawaiian and Pacific Islander (NHPI) people are usually aggregated, masking substantial variation within this heterogeneous population. Herein, the American Cancer Society reports cancer incidence and survival for 8 Asian American and 3 NHPI ethnic groups. METHODS: The authors used population-based cancer registry data from the National Cancer Institute's Surveillance, Epidemiology, and End Results program, for Asian American and NHPI ethnic groups from 2000 through 2022. RESULTS: During 2018-2022, overall cancer incidence ranged from 218.3 per 100,000 Kampuchean people to 474.5 per 100,000 Native Hawaiian people, which was 1.5 times higher than the rate for the aggregated Asian American and NHPI population (307.3 per 100,000). High incidence among Native Hawaiian people is largely driven by the highest rates of female breast, colorectal, and prostate cancers, whereas infection-related cancers were highest among Asian American ethnic groups. For example, liver and stomach cancer incidence is highest among Vietnamese (22.2 per 100,000) and Korean people (17.8 per 100,000), respectively, both of which were nearly twice that in Native Hawaiian people (12.9 and 9.6 per 100,000, respectively). Native Hawaiian and Samoan women are twice and 3 times as likely, respectively, to be diagnosed with uterine corpus cancer as aggregated Asian American and NHPI women or White women. Five-year relative survival ranges from 42% in Laotians to 74% in Asian Indians/Pakistanis, with largest differences for colorectal (43% in Laotians to 72% in Asian Indians/Pakistanis) and prostate (63% in Kampucheans to 97% in Japanese) cancers. CONCLUSIONS: Wide variation in cancer risk within the Asian American and NHPI population highlights the critical need for disaggregated data to effectively target cancer prevention and control interventions.

Adolescent↗

PubMed2026

Pictographs: feasibility and acceptability of a novel method of newborn identification to reduce wrong-patient errors in the NICU.

Wrong-patient errors cause serious harm in newborns. These errors involve ordering and administering tests, procedures, medications, and breast milk to an unintended patient. Newborns receiving care in neonatal intensive care units (NICUs) are at particularly high risk. Although more distinct newborn naming conventions as recommended by the Joint Commission significantly reduce wrong-patient orders, name similarities among multiple-birth infants and truncation of differentiating information in some electronic health record (EHR) systems contribute to this persistent increased risk. Accordingly, novel newborn identifiers are urgently needed. We propose Pictographs - images that are appealing, recognizable, and appropriate - to serve as visual identifiers for newborns in NICUs. Pictographs are selected by caregivers, uploaded into the EHR, and displayed at bedside. As part of a multicenter randomized controlled trial assessing effectiveness of Pictographs to prevent wrong-patient order errors, we initially evaluated feasibility and acceptability of Pictographs at two study sites. Pictographs as novel visual identifiers for newborns in the NICU were generally well received by caregivers and clinicians, and the vast majority of caregivers selected a Pictograph for their infant(s), which was posted at the bedside and uploaded into the EHR. Ordering clinicians - the primary target of the intervention to prevent wrong-patient errors - recognized the potential for Pictographs to provide a visual cue when placing orders, particularly for multiple-birth infants. Here, we describe the rationale, implementation, framework, feasibility, usefulness, and acceptability of Pictographs among key stakeholders. If found effective for preventing wrong-patient errors, Pictographs could be adopted as a patient safety solution in hospitals worldwide.

Female↗

PubMed2026

Self-Report Health Screening Tools in Female Athletes: A Systematic Review of Domain Coverage, Validation, and Use Across Participation Levels.

BACKGROUND: Female athlete health encompasses multiple interconnected domains; however, the self-report screening tools used to assess these domains have not been comprehensively synthesised. OBJECTIVE: To systematically identify self-report health screening tools used to assess female athlete health, map domain coverage, determine validation reporting, and describe application across participation levels. METHODS: This systematic review was pre-registered with PROSPERO ( CRD420251056910 ) and conducted in accordance with PRISMA guidelines. Four databases (PubMed, MEDLINE, SPORTDiscus and Web of Science) were searched from inception to January 2026 using female health and screening-related terms. Methodological quality was appraised using Joanna Briggs Institute and National Institutes of Health tools, and findings were synthesised descriptively. Eligible, peer-reviewed studies reported the use, development or validation of self-report health screening tools assessing one or more domains relevant to female health applied in female athlete populations, spanning recreational through elite participation levels. All sports and activities were included. The search was restricted to English language with no date limits. RESULTS: In total, 360 studies (1990-2026) representing 134,506 female participants spanning recreational to elite sport and 273 screening tools were included. Mental health (n = 77, 34.1%), disordered eating (n = 33, 14.6%) and body image (n = 30, 13.3%) predominated. Domains related to female health, including menstrual health, pelvic floor health, pregnancy/postpartum and breast health were comparatively underrepresented. Most studies reported tools were used for risk identification (n = 323, 80.3%). Validation reporting was inconsistent, with half (n = 180, 50%) reporting use of at least one validated tool. Tool use was concentrated in professional and elite sport, with limited inclusion of recreational, masters and disability athlete cohorts. Health literacy constructs were explicitly assessed in 12.5% of studies (n = 45). CONCLUSIONS: Health screening in female athlete populations remains fragmented and uneven in domain coverage, with inconsistent validation reporting. Development of integrated, multi-domain and contextually inclusive screening frameworks is warranted.

Journal Article↗

PubMed2026

Antibody-drug conjugates against multidrug-resistant cancers: Biomarker-guided patient selection, payload engineering, linker chemistry, and bystander effects.

Antibody-drug conjugates (ADCs) are one of the most significant advancements in modern cancer therapeutics. Combining the target selectivity of monoclonal antibodies with the cytotoxic potential of payloads, ADCs effectively kill cancer cells and offer hope to patients with even refractory cancer types. Beyond simply increasing the number of therapeutic options available for cancer patients, ADCs have become a powerful frontline agent in overcoming multidrug resistance (MDR). As one of the most challenging obstacles to effective cancer care, MDR is mediated by ATP-binding cassette (ABC) transporter-mediated drug efflux, target-based mutations, and dysregulated apoptosis. The clinical success of ADCs specifically engineered to overcome MDR, including in heterogeneous tumors and cancer cells that exhibit bypass signaling, is well established. This is especially evident with trastuzumab deruxtecan (T-DXd) in HER2-low, HER2-positive, and HER2-mutant cancers; sacituzumab govitecan (SG) in TROP2-expressing triple-negative breast cancer (TNBC) and urothelial carcinoma; and enfortumab vedotin in Nectin-4-positive bladder cancer. By overcoming MDR, ADCs have enabled more effective treatment algorithms across multiple malignancies. Most importantly, the clinical application of ADCs has become inextricably linked to cancer genomics. HER2 testing has evolved from a two-tiered system to a continuous spectrum including HER2-ultralow, HER2-low, HER2-positive, and ERBB2-mutant categories. Each of these categories exhibits different eligibility guidelines for ADC patient selection. As cancer cells continue to evolve and develop resistance to even ADCs through mutations and variants, researchers and clinicians have used pharmacogenomics to predict ADC response and resistance. To define the genomic architecture of ADC-resistant tumor subpopulations, single-cell transcriptomic studies and liquid biopsy approaches are being used to enable real-time examination of the tumor genome during ADC therapy, thereby optimizing treatment and circumventing resistance driven by emerging mutations and variants. This review provides a comprehensive analysis of the molecular structure of ADCs, the pharmacological principles underlying their potent cytotoxic activity against MDR cancer cells, the genomic and transcriptomic biomarkers that guide ADC patient selection, and the emerging resistance mechanisms that will shape the next generation of promising ADC development.

Humans↗