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Instead of adding even more burdens to medical practices, artificial intelligence (AI) technology promises to become a tool for a host of clinical needs.

For example, a new report published in JAMA Network Open suggests that AI technology can significantly change medical practice. Physician investigators at Beth Israel Deaconess Medical Center in Boston, Massachusetts, compared a chatbot’s probabilistic reasoning to that of human clinicians. The findings suggest that AI could serve as a useful clinical decision support tool for physicians.

Lead author Adam Rodman, MD, an internist at Beth Israel, said clinicians struggle with probabilistic reasoning, the practice of making decisions based on calculating odds. He and his colleagues evaluated probabilistic reasoning in isolation. They used a previously published national survey of more than 550 practitioners performing probabilistic reasoning on 5 medical cases. Dr Rodman’s team fed the publicly available large language model (LLM) Chat GPT-4 the same series of cases and ran an identical prompt 100 times to generate a range of responses.

The chatbot was tasked with estimating the likelihood of a given diagnosis based on patients’ presentations. Then the chatbot program updated its estimates after given test results, such as chest radiography for pneumonia, mammography for breast cancer, stress test for coronary artery disease, and a urine culture for urinary tract infection.

When test results were positive, it was almost a draw. The chatbot was more accurate in making diagnoses than human clinicians in 2 cases, similarly accurate in 2 cases, and less accurate in 1 case. When tests came back negative, however, the chatbot demonstrated greater accuracy in making diagnoses than human clinicians in all 5 cases.

Probabilistic Reasoning

“I was surprised by these findings,” Dr Rodman said. “Humans do a very poor job at probabilistic reasoning. Whether it's playing poker, being more scared of flying on an airplane than driving on the highway, filling out an NCAA tournament bracket, or for my purposes predicting whether or not a patient has a pneumonia. We have known about innumeracy for a very long time.”

LLMs are effectively word or token prediction engines built off massive amounts of human text. But they also have emergent properties and may help with differential diagnoses. “In terms of routine use, I think physicians will first interact with LLMs in so-called ‘clerical’ tasks, serving as an AI scribe while in the clinic, assisting with discharge summaries, assisting with many of the other rote tasks that can take up so much time in the day,” Dr  Rodman said.

Over the next several years, Dr Rodman said, he expects AI to start making a significant impact in clinical care in the form of clinical decision support. “I imagine LLMs that serve as a co-pilot, looking for early signs of medical errors, making suggestions on additional information to collect or additional diagnoses to consider or even taking the first pass at collecting a history,” he said.

During graduate school at Stanford University in Palo Alto, California, Sarah Hooper, PhD, developed ways to improve the automated processing of cardiac MRIs. Now, as a research scientist at the National Heart, Lung, and Blood Institute’s Imaging AI program, she is working to integrate machine learning across a variety of imaging platforms.

Dr Hooper said machine learning can be inserted into any point of the imaging pipeline to make things more efficient. One program might make it easier to automate parts of the analysis workflow so that a radiologist can spend 5 minutes looking at an image instead of 30. That all translates into patients getting results faster, according to Dr Hooper.

Predicting Cancer Outcomes

Researchers at UT Southwestern Medical Center in Dallas have developed an AI model that analyzes the spatial arrangement of cells in tissue samples. This approach, detailed in Nature Communications, accurately predicted outcomes for cancer patients, marking a significant advancement in using AI for cancer prognosis and personalized treatment strategies.

Tissue samples analyses by pathologists is time-consuming, and interpretations can vary among pathologists. In addition, the human brain can miss subtle features present in pathology images that might provide important clues to a patient’s condition. The new AI model mimics how pathologists read tissue slides, starting with detecting cells in images and their positions. From there, it identifies cell types as well as their morphology and spatial distribution, creating a map in which the arrangement, distribution, and interactions of cells can be analyzed.

The investigators successfully applied this tool to 3 clinical scenarios using pathology slides. They now hope to adopt this model to streamline targeted preventive measures for high-risk populations and optimize treatment selection for individual patients.

Investigators at Arizona State University School of Biological and Health Systems Engineering in Tempe are using AI to sort through decades of medical data to identify treatments for neurological disorders. They are also applying AI models to learn how cancer cells replicate and find solutions to keep older adults safe from life-threatening falls.

One of the investigators, associate professor Bradley Greger, PhD, said that for individual patient care, AI will be useful in digesting large amounts of data from multiple tests, physical exams, and imaging to aid clinical decisions. “Just like any technology, MRI, X-ray, ECG, blood tests, etc., AI can help to improve outcomes for patients through reducing morbidity and mortality,” Dr Greger said.

Dr Rodman agrees and said there are many examples where AI may help improve outcomes and possibly quality of life. “I can imagine a few ways language models can help with morbidity and mortality in the short-to-medium run. The first is in medical errors,” he said. “The second is in minimizing misdiagnosis and delayed diagnosis. We already have good experimental data that LLMs can make diagnoses better than humans and I'm running studies now showing how the use of LLMs actually changes human behavior,” said Dr. Rodman. 

Patient Triage

Within the next several years, he envisions there will be human trials with AI providing a "second opinion." AI is perfectly suited for triaging patients and patient navigation. Health systems have a vested interest in both triaging patients to the right place for safety, and navigating them to the right place for efficiency. These systems currently rely on a considerable amount of manpower.

Triage decisions are high stakes, so there would need to be a high bar for evidence to show that LLMs can perform in this domain, Dr Rodman said. “But that’s what is exciting. Even if imperfect, their ease of use and ability to be integrated into clinical workflows could theoretically make humans make better decisions.”

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Stereotactic ablative body radiotherapy (SABR) is safe and effective treatment for older patients who have kidney cancer but are not suitable candidates for surgery, according to a recent study.

The new finding is from the phase 2 prospective, nonrandomized TransTasman Radiation Oncology Group (TROG) FASTRACK II trial (ClinicalTrials.gov ID: NCT02613819). Besides an exceptional cancer control rate for relatively large cancers (average 4.7 cm), there were no cancer-related deaths and only modest renal function decline after treatment, said lead investigator Shankar Siva, MBBS, PhD, a radiation oncologist who presented the findings at the American Society for Radiation Oncology (ASTRO) 2023 Annual Meeting. There is a significant unmet need for curing patients with tumors of these sizes, and these new findings point to the potential of radiation therapy to address that need, he said.

“Our trial benchmark for success was a control rate of greater than 80%, and we were pleasantly surprised that there was a 100% control rate, which is unprecedented in cancers of this size,” said Dr Siva, a professor in the Department of Radiation Oncology at the Peter MacCallum Cancer Centre in Melbourne, Australia. He noted that older patients with primary renal cell carcinoma (RCC) have unique challenges that make it difficult to treat them surgically.

“We are able to offer a new novel standard of care,” Dr Siva said. “This is the largest trial of a nonsurgical curative option in patients with primary RCC.”

The trial included 70 patients with a median age of 77 years. All had inoperable, high-risk kidney tumors or declined surgery. The median follow-up was 42 months. The majority of patients were male (70%) and the median body mass index was 32 kg/m2. The median Charlson comorbidity score was 7; the median RENAL complexity score was 8.

SABR was delivered in 1 or 3 sessions at 7 Australian centers and 1 in the Netherlands. Treated tumors on average were 4.7 centimeters. Of the 70 patients, 23 who had tumors smaller than 4 cm received a single fraction of radiation and 47 who had tumors larger than 4 cm received 3 fractions. No patient experienced local failure or died from their cancer. Dr Siva said. Freedom from distant failure was 99% at 1 and 3 years. Overall survival was 99% at 1 year after SABR and 82% at 3 years.

Adverse events (AEs) were relatively modest, with no grade 4 or 5 toxicities observed. However, 7 patients (10%) experienced grade 3 adverse events, most commonly transient abdominal pain (3 patients). In this study, 51 patients (73%) had a grade 1-2 treatment-related event and 11 patients (16%) experienced no AEs.

The average estimated glomerular filtration rate (eGFR) declined by 10.8 mL/min/1.73 m2 at 1 year and 14.6 mL/min/1.73 m2 at 2 years after treatment, indicating mild-to-moderate kidney stress. Only 1 patient required dialysis following treatment. Kidney function decreased modestly, leveling off after 2 years, Dr Siva said. “Most of these patients did not have a curative option,” Dr Siva said.

The findings justify designing a randomized phase 3 trial to compare SABR with surgery as the primary treatment modality for patients with operable kidney cancer, he said.

“The outcomes were excellent, with a very good toxicity profile, including transient grade 3 side effects and mild drop in renal function,” said Anand Mahdevan, MD, from the Department of Radiation Oncology at NYU Grossman School of Medicine in New York. “Future randomized trials for local therapy of kidney cancer should include SABR as a therapeutic option.”

“We now have the first international, multi-center prospective clinical trial in this space,” said Rohann Correa MD, PhD, of the London Health Sciences Centre in the Ontario, Canada. As far as Dr Correa is aware, there is not a comparable level of evidence for any other ablative modalities, particularly for tumors larger than 3 cm.

The trial provides sufficient evidence to influence clinical practice for patients who are unable or unwilling to undergo surgery, Dr Correa said.

Ellen Kim, MD, MPH, Director of Clinical Informatics in the Department of Radiation Oncology at Dana-Farber Cancer Institute in Boston, Massachusetts, noted the trial is relatively small, with only 70 patients. However, patients were recruited from 8 centers over nearly 4 years. “When available, SABR should certainly be considered for medically inoperable patients with this disease,” Dr Kim said. Future studies will be needed to confirm long-term safety, efficacy, and optimal SABR treatment techniques (such as dose/fractionation, immobilization, and expansion), she said.

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In individual patients, an estimated glomerular filtration rate (eGFR) based on serum creatinine and/or cystatin C often differs substantially from measured GFR (mGFR), investigators reported in the Annals of Internal Medicine.

The individual-level difference between mGFR and eGFR is large, according to Tariq Shafi, MBBS, MHS, of The University of Mississippi Medical Center in Jackson, Mississippi, and colleagues. "Clinicians need to recognize that the eGFR is not an mGFR replacement and consider eGFR's inaccuracy while managing individual patients."

In analyses of data from 3223 participants across 4 studies, the investigators found that only 37% of eGFR results based on creatinine (eGFRCR) fell within 10% of mGFR. For example, at an eGFRCR of 45 mL/min/1.73 m2, 15% of the participants had an mGFR outside of the range of 30-60 mL/min/1.73 m2, 30% had an mGFR outside the range of 35-45 mL/min/1.73 m2, and 57% had an mGFR outside the range of 40-50 mL/min/1.73 m2. Such discrepancies between measured and estimated GFR were observed regardless of an individual's race, age, or sex.

The agreement in chronic kidney disease (CKD) staging between mGFR and eGFRCR was only 58% overall, Dr Shafi's team reported. Among the 42% of patients who were misclassified, 22% were reclassified to a lower CKD stage and 20% to a higher stage. For 39%, the misclassification was by 1 CKD stage.

The eGFR equations incorporating cystatin C did not improve the probability of large errors and CKD stage misclassification. The investigators pointed out that non-GFR factors influence the serum concentration of creatinine and/or cystatin C, such as obesity, muscle mass, meat consumption, and fasting.

Findings Poised to Change Clinical Practice

The clinical implications of these findings are far-reaching. Underestimating GFR may exclude patients from receiving optimal therapies and overestimating GFR may leave patients vulnerable to drug adverse effects such as hyperkalemia from mineralocorticoid antagonists and toxicity from chemotherapy, Dr Shafi's team pointed out.

In an interview with Renal & Urology News, Christine A. White, MD, MSc, of Queen's University in Kingston, Ontario, Canada, who was not involved in the study, said the research by Dr Shafi and colleagues “exposes the substantial discrepancy that often exists between estimated GFR using creatinine or cystatin C and measured GFR in individuals. This discrepancy is not captured by the traditionally reported metric of overall population bias where individual positive and negative biases negate each other, leading to an erroneous impression of unbiased GFR estimation at the individual level.

"The discrepancy,” she continued, “has not been well appreciated by clinicians assessing patients’ kidney function who then make work-up and treatment decisions according to eGFR, nor is it explicitly addressed in many society clinical practice guidelines.”

Dr White said the study authors appropriately recommend that the uncertainty of eGFR be reported by laboratories alongside eGFR results and that GFR measurement should become more widespread. Dr White will be conducting a session on GFR measurement techniques at the American Society of Nephrology's Kidney Week in November 2022.

"There are many ways to measure GFR using either renal or plasma clearance of a variety of exogenous markers with different sampling strategies," she said. Few comparative studies have evaluated various protocols against the gold standard renal inulin clearance, which is no longer commercially available, she noted.

"Available studies indicate that GFR measurement protocols should be tailored according to specific patient characteristics such as level of eGFR and presence of edema," Dr White said.

Iohexol has several advantages over other tracers, she explained. It is non-radioactive, inexpensive, and already in use worldwide as a contrast media, so it is "poised to become a preferred tracer."

According to Dr White, "Studies such as this one may galvanize the development of GFR measurement protocols that are both accurate and logistically and economically feasible across the spectrum of GFR and clinical presentations."

The study authors noted that advances in nonradiolabeled GFR measurement techniques have made it a "highly feasible" and safe outpatient procedure. Race, sex, age, and socioeconomic factors should not cause errors, although results may vary due to normal physiology and measurement errors, such as incomplete bladder emptying. It should be a "priority" and made "widely available," they wrote.

The 4 cohorts in this study included GENOA (Genetic Epidemiology Network of Arteriopathy), ALTOLD (Assessing Long Term Outcomes in Living Kidney Donors), ECAC (Epidemiology of Coronary Artery Calcification), and CRIC (Chronic Renal Insufficiency Cohort). Overall, 58% of participants were White, 32% Black, 7% Hispanic, and 3% another race. The GFR was directly measured using urinary clearance of nonradiolabeled iothalamate in GENOA and ECAC, radiolabeled iothalamate in CRIC, and plasma clearance of iohexol in ALTOLD.

The investigators calculated eGFRCR using the Chronic Kidney Disease Epidemiology (CKD-EPI) 2021 race-free equation, which is valid only in adults, and the European Kidney Function Consortium (EKFC) equation, which is valid in individuals aged 2 years or older. They calculated the eGFR from serum cystatin C (eGFRCYS) and from serum creatinine and serum cystatin C combined (eGFRCR-CYS) using the CKD-EPI 2012 and 2021 equations, respectively.

Reference

Shafi T, Zhu X, Lirette ST, et al. Quantifying individual-level inaccuracy in glomerular filtration rate estimation: a cross-sectional study. Ann Intern Med. Published online July 4, 2022. doi:10.7326/M22-0610

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Tobacco smoking rates have declined over recent decades but tobacco use remains a leading cause of cancer. Smoking causes 1 in 5 cancers overall and nearly one-third of all cancer deaths in the United States.1 The association is particularly stark for lung cancers, more than 80% of which are caused by tobacco.1 

Continued smoking after a cancer diagnosis is a significant challenge for successful treatment, including radiotherapy, reducing complete response rates and quality of life, and increasing the risk of radiation toxicities and complications, locoregional tumor recurrence, second cancers, and death.2-8 A systematic review of data from 71 studies found that smoking during adjuvant breast cancer radiotherapy is associated with skin reactions and worse cardiovascular, lung function, and breast reconstruction outcomes, and a higher risk of secondary carcinomas and death.4  

Tobacco smoke contains more than 4000 chemicals, including arsenic, benzene, cadmium, formaldehyde, hydrogen cyanide, lead, and other known carcinogens.5 Collectively, this complexly toxic chemical mixture renders cancer treatments — including radiotherapy, chemotherapy, and surgery — less effective and more toxic, while altering tumor biology in ways that can make malignancies more aggressive.2,5-8 Smoking constricts blood vessels, reducing oxygen perfusion; upregulates inflammatory and tumor signaling pathways associated with proliferation, angiogenesis, and tissue invasion; increases the risk of tumor cell radioresistance; impairs tissue healing processes; and worsens radiation toxicities such as mucositis, xerostomia, diarrhea, and weight loss.3,5,7 

Compared to patients who quit smoking at the time of a cancer diagnosis, smokers undergoing cancer treatment have poorer overall survival and more adverse events.9 

Surprisingly, given its critical importance for patient outcomes, the molecular pathways and impacts of continued tobacco use and how a patient’s smoking status and history should guide treatment decisions remain poorly understood.8-10 These gaps do not mean the connection between continued smoking and poorer outcomes is in doubt, but they do need to be studied to better understand how to optimize treatments informed by patient smoking status and history.

“Several studies have demonstrated a clear correlation between smoking and the response to radiation or chemoradiation therapy in various cancers,” explained Srikumar Chellappan, MD, of the H. Lee Moffitt Cancer Center in Tampa, Florida, in a 2022 review of how smoking cessation enhances therapeutic responses.9 “While the underlying molecular mechanisms have not been fully elucidated, the poor response to radiotherapy has been prevalent across several cancer types, indicating that it is a genuine correlation.”

The International Association for the Study of Lung Cancer (IASLC) recently called for more systematic collection of data on patients’ tobacco smoking and smoking cessation efforts in clinical trials to help close that evidence gap.8,10 In 80% of cases, tobacco use data is not collected at baseline (enrollment) in clinical cancer trials. In those trials that do gather the data, it frequently goes unanalyzed.8 Smoking frequency is rarely collected.8 Worse yet, consistent definitions are not implemented across studies, and even how best to ask patients about their tobacco use is unclear.8,10 

IASLC recommendations including documentation of tobacco use with standard definitions used in the validated Cancer Patient Tobacco Use Questionnaire (C-TUQ) when patients enroll to participate in a clinical trial, and to document all tobacco use, including e-cigarettes, smoking cessation efforts, and to analyze how tobacco use and cessation correlate with response rates, survival, adverse events, and quality of life.8,10   

"
There's a whole host of things that negatively impact radiation therapy, and increase toxicity from the radiation for those who continue to smoke.

“There are short-term and long-term effects, because radiation induces more inflammation in the smoker, in the tissues that are in the radiation field,” said William Evans, MD, professor emeritus of Oncology at McMaster University in Ontario, Canada, and a coauthor of the IASLC recommendations [interview; March 5, 2024]. “There's a whole host of things that negatively impact radiation therapy, and increase toxicity from the radiation for those who continue to smoke.” 

Those impacts vary between cancer types and irradiated anatomies, Dr Evans noted. 

“Radiation for laryngeal cancer causes more radiation reaction mucositis in the vocal cords and throat in the treatment field and a weaker voice, generally speaking, at the end of treatment,” he explained. “Radiating the pelvis, say for endometrial cancer, ovarian cancer, or prostate cancer, there's the small bowel, large bowel, and bladder in the radiotherapy fields. All of those will have more inflammation which increases acute symptoms like diarrhea or frequency of painful urination, but they also can lead to long-term effects — more scarring, so that you could end up with a more contracted bladder and hence urinary symptoms on an ongoing basis after the healing occurs to the mucosa and the same in the bowels.” 

Smoking Cessation

There are numerous smoking cessation strategies, which can be broken down into 5 general categories11,12:

  • Nicotine replacement pharmacotherapy (NRT) Provides controlled-dose nicotine to curb cravings without exposure to toxic tobacco smoke
  • Behavioral counseling Psychological support and education, including stress management strategies. Practices vary but can include a single session or sustained counseling throughout cancer treatment
  • Social support Education of patients, their family and caregivers, and cancer care clinicians to support patient efforts to quit smoking through encouragement and reminders
  • Quit plans A structured step-by-step plan for quitting smoking, anticipating and planning for challenges
  • High-intensity or combined interventions These approaches combine behavioral, social support, and pharmacotherapeutic strategies

As with the effects on cancer treatment of continued smoking, the benefits of smoking cessation at diagnosis, as well as the best approaches to cessation, urgently need more high-quality, well-designed trials. A 2024 meta-analysis of data from 72 studies, 19 of which were randomized, controlled clinical trials, by researchers in the Netherlands found that methodologic quality is generally poor.12 However, what is known so far strongly supports benefits to patients.12,13 For example, among people with head and neck cancer, for which cigarette smoking is the leading risk factor, quitting at diagnosis is associated with better overall survival.13 

In a meta-analysis of a subset of relatively high-quality studies (18 randomized controlled trials and 3 observational studies), the Dutch authors of the 2024 meta-analysis found significant benefits to patients of smoking cessation interventions based on behavioral interventions or combined-modality (behavioral support plus pharmacotherapy) interventions, but not for pharmacologic interventions alone.12 

High-intensity combination pharmacotherapeutic and behavioral interventions (sustained counseling during treatment and free smoking-cessation medication) is associated with a 67% greater success rate than telephone counseling and medication advice.12,14  

Integrating comprehensive smoking cessation care into clinical oncology can be time consuming and expensive. But given the stakes, and compared to less effective and more toxic cancer treatment, it is money well spent, experts say.  

Radiation oncology teams and oncology nurses can lead the way, motivating, educating, and assisting patients, and providing or advocating for patient referrals to sustained tobacco cessation support.15-18 The Oncology Nursing Society and US National Heart, Lung, and Blood Institute Smoking Education Program offer advice about how oncology nurses can play a significant role in smoking cessation.18,19

Sustained interventions are key: patients very frequently resume smoking by 12 months after cessation interventions.17 Step one is recording smoking status and history and offering smoking cessation support to all patients undergoing radiotherapy. Patients with prostate or breast cancer are less frequently offered smoking-cessation care.16 Smoking history is recorded less frequently for patients with prostate cancer (65% of the time) than for patients with breast (91%), head and neck (96%), or lung (97%) cancers, according to a 2020 study at the Oregon Health & Science University in Portland.16 

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