13 research outputs found

    Predicting per-lesion local recurrence in locally advanced non-small cell lung cancer following definitive radiation therapy using pre- and mid-treatment metabolic tumor volume

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    Background: We evaluated whether pre- and mid-treatment metabolic tumor volume (MTV) predicts per lesion local recurrence (LR) in patients treated with definitive radiation therapy (RT, dose≥60 Gy) for locally advanced non-small cell lung cancer (NSCLC). Methods: We retrospectively reviewed records of patients with stage III NSCLC treated from 2006 to 2018 with pre- and mid-RT PET-CT. We measured the MTV of treated lesions on the pre-RT (MTVpre) and mid-RT (MTVmid) PET-CT. LR was defined per lesion as recurrence within the planning target volume. Receiver operating characteristic (ROC) curves, cumulative incidence rates, and uni- and multivariable (MVA) competing risk regressions were used to evaluate the association between MTV and LR. Results: We identified 111 patients with 387 lesions (112 lung tumors and 275 lymph nodes). Median age was 68 years, 69.4% were male, 46.8% had adenocarcinoma, 39.6% had squamous cell carcinoma, and 95.5% received concurrent chemotherapy. Median follow-up was 38.7 months. 3-year overall survival was 42.3%. 3-year cumulative incidence of LR was 26.8% per patient and 11.9% per lesion. Both MTVpre and MTVmid were predictive of LR by ROC (AUC = 0.71 and 0.76, respectively) and were significantly associated with LR on MVA (P = 0.004 and P = 7.1e-5, respectively). Among lesions at lower risk of LR based on MTVpre, higher MTVmid was associated with LR (P = 0.001). Conclusion: Per-lesion, larger MTVpre and MTVmid predicted for increased risk of LR. MTVmid was more highly predictive of LR than MTVpre and if validated may allow for further discrimination of high-risk lesions at mid-RT informing dose painting strategies

    Evaluation of GPT-3.5 and GPT-4 for supporting real-world information needs in healthcare delivery

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    Despite growing interest in using large language models (LLMs) in healthcare, current explorations do not assess the real-world utility and safety of LLMs in clinical settings. Our objective was to determine whether two LLMs can serve information needs submitted by physicians as questions to an informatics consultation service in a safe and concordant manner. Sixty six questions from an informatics consult service were submitted to GPT-3.5 and GPT-4 via simple prompts. 12 physicians assessed the LLM responses' possibility of patient harm and concordance with existing reports from an informatics consultation service. Physician assessments were summarized based on majority vote. For no questions did a majority of physicians deem either LLM response as harmful. For GPT-3.5, responses to 8 questions were concordant with the informatics consult report, 20 discordant, and 9 were unable to be assessed. There were 29 responses with no majority on "Agree", "Disagree", and "Unable to assess". For GPT-4, responses to 13 questions were concordant, 15 discordant, and 3 were unable to be assessed. There were 35 responses with no majority. Responses from both LLMs were largely devoid of overt harm, but less than 20% of the responses agreed with an answer from an informatics consultation service, responses contained hallucinated references, and physicians were divided on what constitutes harm. These results suggest that while general purpose LLMs are able to provide safe and credible responses, they often do not meet the specific information need of a given question. A definitive evaluation of the usefulness of LLMs in healthcare settings will likely require additional research on prompt engineering, calibration, and custom-tailoring of general purpose models.Comment: 27 pages including supplemental informatio

    Biopolymer based nanofertilizers applications in abiotic stress (drought and salinity) control

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    With ever growing world population, environmental changes, uncontrolled urbanization, food security is emerging as an important issue with every passing day. Researchers from divergent fields including plant sciences are developing strategies and technologies to restrict the problem of food security. Plant stresses such as drought and salinity can be termed as key players in the alleviation of overall crop yield around the world. Both the stresses hit the nutrient uptake ability of the plant leaving it venerable to environmental conditions. Nano fertilizers are emerging at a new solution for handling the major plant problems like salinity and drought. The application of nanoparticles has advantages such as enhanced surface area and enhanced reactivity. The safe, targeted and slow delivery of plant nutrients can be carried-out by using bio-based nanoparticle carriers. A large variety of biopolymers have been tested for this purpose such as chitosan, cellulose, alginate and chitin. In the current book chapter, we provide an overview of the basic concepts of Nano fertilizers and its role in alleviation of salinity and drought stress. Also, the control release of these Nano fertilizers through different matrices have been discussed in detail with recent studies

    Cellulose-based hydrogel materials: chemistry, properties and their prospective applications

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