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In this randomized trial of the postoperative treatment of high-risk squamous-cell carcinoma of the head and neck, concurrent radiotherapy plus chemotherapy (cisplatin) reduced the incidence of local and regional recurrence and prolonged disease-free survival, as compared with radiotherapy alone. The combined treatment was substantially more toxic than radiotherapy alone. Concurrent radiotherapy plus chemotherapy (cisplatin) reduced the incidence of recurrence and prolonged disease-free survival. Despite regimens that permit organ preservation in selected patients with advanced carcinomas of the head and neck, 1 – 3 ablative surgical resection and postoperative radiotherapy are required in many patients. Typically, local or regional disease recurs in 30 percent of patients, and distant metastases appear in 25 percent; the five-year survival rate is 40 percent. 4 Patients who have two or more regional lymph nodes involved, extracapsular spread of disease, or microscopically involved mucosal margins of resection have particularly high rates of local recurrence (27 to 61 percent) and distant metastases (18 to 21 percent) and a high risk of death (five-year . . .

Available preclinical and phase 2 clinical data suggest that the addition of cetuximab, a monoclonal antibody directed against the epidermal growth factor receptor (EGFR), to chemotherapy might improve outcome in patients with advanced non-small-cell lung cancer (NSCLC). We aimed to assess whether the addition of cetuximab to chemotherapy improved progression-free survival in patients with recurrent or progressive NSCLC after platinum-based therapy. In this unmasked, open-label randomised phase 3 trial we enrolled patients with metastatic, unresectable, or locally advanced NSCLC from 121 sites in Canada and the USA. Eligible patients were those aged 18 years or older who had experienced progressive disease during or after one previous platinum-based regimen. Initially, patients were randomly assigned to receive either pemetrexed (500 mg/m2) or docetaxel (75 mg/m2) and then randomly assigned within each group to receive their chemotherapy with or without cetuximab (400 mg/m2 at first dose and 250 mg/m2 weekly thereafter) until disease progression or unacceptable toxicity. However, after a change in the standard of care, investigators chose whether to treat with pemetrexed or docetaxel on a patient-by-patient basis. The primary analysis was changed to compare progression-free survival with cetuximab plus pemetrexed versus pemetrexed, on an intention-to-treat basis. This study is registered with ClinicalTrials.gov, number NCT00095199. Between Jan 10, 2005, and Feb 10, 2010, we enrolled 939 patients; data for one patient was accidentally discarded. Of the remaining 938 patients, 605 received pemetrexed (301 patients with cetuximab and 304 alone) and 333 received docetaxel (167 in combination with cetuximab and 166 alone). Median progression-free survival with cetuximab plus pemetrexed was 2·9 months (95% CI 2·7–3·2) versus 2·8 months (2·5–3·3) with pemetrexed (HR 1·03, 95% CI 0·87–1·21; p=0·76). The most common grade 3–4 adverse events with cetuximab plus pemetrexed were fatigue (33 [11%] of 292 patients), acneiform rash (31 [11%]), dyspnoea (29 [10%]), and decreased neutrophil count (28 [10%]), and with pemetrexed alone were dyspnoea (35 [12%] of 289 patients), decreased neutrophil count (26 [9%]), and fatigue (23 [8%]). A significantly higher proportion of patients in the cetuximab plus pemetrexed group (119 [41%] of 292 patients) experienced at least one serious adverse event than those patients in the pemetrexed group (85 [29%] of 289 patients; p=0·0054). Nine (3%) of 292 treated patients in the cetuximab and pemetrexed group died of adverse events compared with five (2%) of 289 treated patients in the pemetrexed alone group. The use of cetuximab is not recommended in combination with chemotherapy in patients previously treated with platinum-based therapy. Eli Lilly and Company and ImClone Systems LLC, a wholly owned subsidiary of Eli Lilly and Company.

Prospective clinical trials have been the cornerstone for testing new therapies in medicine for several centuries, dating back at least to James Lind who is acknowledged for conducting the first such study for the treatment of scurvy in 1747. Randomization has also been firmly established as a means to minimize bias and enhance precision when two or more therapeutic interventions are being compared to each other. Traditionally, the randomization allocation in a particular clinical trial is fixed throughout the duration of the trial, using either a balanced approach in which the distribution of patients into each arm is equal (1:1) or an unbalanced schema in which the allotment of patients is unequal (2:1, 3:1, etc.) with the higher number of patients usually being assigned to the experimental arm. A relative newcomer to the clinical trials scene is a trial design using a randomization method referred to as outcome-adaptive randomization (OAR). In this type of comparative clinical trial, the randomization probability is not fixed, but adapts throughout the conduct of the study. Specifically, as clinical outcome data become available, the randomization scheme is modified such that more patients are enrolled in the arm for which the results seem to be more favorable. This adaption of the treatment allocation is fluid, and may go up or down throughout the duration of the trial as more clinical data on the patients who were previously enrolled become available. The ethical intent of OAR is that at the end of the trial, more patients will end up being treated with the better therapy, and thus fewer patients will receive an inferior treatment.

The purpose of this study is to determine whether co-administration of granulocyte colony stimulating factor (G-CSF) and bleomycin results in enhanced pulmonary toxicity compared with bleomycin alone. A retrospective analysis comparing two groups of patients with advanced germ cell tumors receiving combination chemotherapy that includes bleomycin with or without G-CSF. Indiana University Medical Center. Group A consisted of 29 patients with advanced-stage germ cell tumors who were treated with combination chemotherapy that included bleomycin. All patients received concurrent prophylactic G-CSF. Group B consisted of 57 patients with advanced-stage germ cell tumors who were treated on a phase 3 study comparing standard BEP (bleomycin, etoposide, cisplatin) to BEP with twice the cisplatin dose. None of these patients received growth factor. Of the 29 patients who received concurrent chemotherapy and G-CSF, ten (34%; 95% confidence interval [CI], 17.9 to 54.3%) were believed to have clinically significant bleomycin toxicity. Of the 57 patients who did not receive growth factor, 19 (33%; 95% CI, 21.4 to 47.1%) had bleomycin-related toxicity. There was no difference in the incidence of pulmonary toxicity between the groups (p=1.00 by Fisher's Exact Test). There is no increase in pulmonary toxicity with co-administration of G-CSF and bleomycin compared to bleomycin alone in patients with advanced germ cell tumors.

Figure 1. Acid-Fast Organisms. A bone marrow-biopsy specimen, stained by the Ziehl-Neelsen technique (x1000), was obtained from a 47-year-old man with the acquired immunodeficiency syndrome who presented with a high fever and pancytopenia. The small bright-red, rod-shaped cells (arrow) are acid-fast organisms. The larger bright-red areas are clumps of the same organisms. Despite therapy with a combination of ethambutol, clofazimine, rifampin, and ciprofloxacin, the patient died 11 days after the biopsy was performed. Bone marrow cultures subsequently grew Mycobacterium xenopi.

Background Precision medicine promises significant health benefits but faces challenges such as complex data management and analytics, interdisciplinary collaboration, and education of researchers, healthcare professionals, and participants. Addressing these needs requires the integration of computational experts, engineers, designers, and healthcare professionals to develop user-friendly systems and shared terminologies. The widespread adoption of large language models (LLMs) such as Generative Pretrained Transformer (GPT) and Claude highlights the importance of making complex data accessible to non-specialists. Methods We evaluated the Stanford Data Ocean (SDO) precision medicine training program’s learning outcomes, AI Tutor performance, and learner satisfaction by assessing self-rated competency on key learning objectives through pre- and post-learning surveys, along with formative and summative assessment completion rates. We also analyzed AI Tutor accuracy and learners’ self-reported satisfaction, and post-program academic and career impacts. Additionally, we demonstrated the capabilities of the AI Data Visualization tool. Results SDO demonstrates the ability to improve learning outcomes for learners from broad educational and socioeconomic backgrounds with the support of the AI Tutor. The AI Data Visualization tool enables learners to interpret multi-omics and wearable data and replicate research findings. Conclusions SDO strives to mitigate challenges in precision medicine through a scalable, cloud-based platform that supports data management for various data types, advanced research, and personalized learning. SDO provides AI Tutors and AI-powered data visualization tools to enhance educational and research outcomes and make data analysis accessible to users from broad educational backgrounds. By extending engagement and cutting-edge research capabilities globally, SDO particularly benefits economically disadvantaged and historically marginalized communities, fostering interdisciplinary biomedical research and bridging the gap between education and practical application in the biomedical field. Bahmani, Cha, Alavi, Dixit et al. evaluate an AI-facilitated precision medicine learning platform they built, Stanford Data Ocean. The platform, which provided 3594 costfree certification accesses across 93 countries, demonstrates positive training outcomes across bioinformatics topics for low and middle income learners. Plain language summary Precision medicine is the use of various types of health data specific to an individual to improve disease prevention, diagnosis, or treatment. We used artificial intelligence to build a precision medicine learning platform for clinicians and researchers in training. Students in 93 countries accessed the platform and found it helpful. It could be particularly helpful for training students in low- and middle-income countries.