Jane is a 40-year-old, married mother of two teenage boys. She teaches at the local elementary school and has been in good health for most of her life. She has no surgical history. Her most severe ailment up to this point has been the flu at age 27. Her students are first-graders; they are often difficult to control. She also experiences the normal stresses of raising teenagers. Jane takes mile-long walks daily, but historically has indulged in junk food and high-calorie snacks. She set out to change her eating habits and has thus far been successful.
For the past year she has had dyspepsia and vague abdominal discomfort. The onset was after a vacation to Mexico last year. She sometimes thinks that the symptoms are related to anxiety brought on by classroom overcrowding at her school. Initially, she would use Zantac and other over-the-counter H2-blockers and they would provide relief from uncomfortable symptoms such as heartburn. But lately, these non-prescription drugs have not provided reprieve from the pain.
About six months ago, she noted that her clothes felt looser. One morning, Jane stepped onto a scale to learn that she had lost about 20 pounds over the past year and thought this was because of her dieting and better eating. She silently praised herself for her healthy choices.
However, after a few more months co-workers began to notice the continued weight loss. They were concerned with Jane’s appearance and at the encouragement of a peer she went to see her family physician. Laboratory testing showed mild anemia. Her family history was a bit sketchy since her mother had died in a car accident when Jane was just a child. Jane knew little about her mother, and it was difficult to trace her roots as her mother had emigrated from Russia. Jane’s father died of a heart attack two years ago.
Presentation, Examination and Diagnosis
Her family physician made a diagnosis of possible gastritis and started her on twice-daily dosing of a proton pump inhibitor along with dietary changes. Her physician instructed her to stop consuming whole milk, hot cocoa, mint tea, and some of her other favorite beverages. She reluctantly followed these instructions, but there was little change in symptoms. She was then referred to a gastroenterologist.
Clinical Prediction Score for Patient with Involuntary Weight Loss and Nonspecific Symptoms
Criteria for Grading Weight Loss Over a Period of Time
The gastroenterologist performed an upper GI endoscopy (esophagogastroduodenoscopy, or EGD). An ulcerated mass was noted in the gastric fundus, which was biopsied. The pathology report was moderately-differentiated adenocarcinoma.
ALARM Symptoms Indicating Possibility of Cancer in a Patient with Dyspepsia
Gastric Carcinoma Prognostic Score
Postrecurrence Risk Score for Predicting Survival in Patient with Recurrent Gastric Carcinoma
Endoscopic ultrasound (EUS) showed invasion into the muscularis propria but there were no enlarged lymph nodes. A PET scan was negative other than for uptake in the stomach. After discussion with an oncologist the patient received preoperative chemoradiation. This was complicated by nausea and vomiting that was controlled with antiemetics.
Jane’s surgical oncologist performed a gastric resection that included spleen and regional lymph nodes. The resection margins were negative for tumor. Only a small amount of residual tumor was found at the primary site. Twenty lymph nodes were identified and all were negative for metastases. Based on these findings the tumor was staged as pT2N0M0 (Stage 1b).
Prognostic Model for Patients with Gastric Cancer
The cancer was now localized, so the patient underwent chemotherapy after surgery. Six months after completion of therapy she was making a good recovery and was able to exercise. Her appetite was improving but she still needed to restrict her diet to foods that would not cause nausea or discomfort.
Tool for Predicting Acute Chemotherapy-Induced Nausea and Vomiting (CINV)
Tool for Predicting Delayed Chemotherapy-Induced Nausea and Vomiting (CINV)
Karnofsky Performance Scale Index
Because of her relatively young age she was referred to a genetic counselor and an attempt was made to get more information about her mother’s family.
When to Consider the Diagnosis of Familial or Hereditary Cancer
Analytics: Easily Implemented Methods of Diagnosis & Tools for Predicting Risk
Medical algorithms can save lives and assist with diagnosis as showcased here. The Medical Algorithms Company (TMAC) is a world-leading digital resource of 21,000 health analytics physicians can use to address many of the complications that arose in this case.
The case study highlights algorithms for assessing weight loss, predicting cancer risk, and for prognostic purposes. Jane’s family physician, gastroenterologist, and oncologist all could have used these algorithms for more accurate patient assessment.
– Gastric adenocarcinomas can be identified early with the implementation of analytics in clinical practice.
– Medical algorithms, if used strategically and appropriately, can be instrumental in diagnosis, assessment and disease management.
The medical algorithms highlighted in this case study are available at The Medical Algorithms Company and also on the Apervita health analytics platform.
Apervita is the leading health analytics community and marketplace, where prominent health professionals and enterprises from around the globe are transforming the world’s health knowledge into thousands of health analytics.
At Apervita, we believe that health researchers and practitioners have already created the greatest wealth of health knowledge that has ever existed and it is just waiting to be unleashed to improve health. Today, the majority of this knowledge is paper-based or locked into proprietary systems. The Apervita community is already unlocking them, turning them into computable and shareable analytics and putting them to work to improve health. They are addressing some of the biggest health challenges, such as the 100,000s of patients that die prematurely every year in the United States from chronic disease, complications and preventable adverse events.
Apervita is a secure, self-service platform, that enables health professionals and enterprises to author, publish and subscribe to a market of evidence-based algorithms, quality and safety measures, pathways, and protocols, easily connecting them to data and workflow. Available to every health professional and powerful enough for the entire health enterprise, Apervita provides health analytics at a tenth of today’s cost, in a hundredth of the time.
About the Authors
Farva Jafri is a manager at Apervita, Inc. on the Content & Authoring and Legal teams. She has a Juris Doctorate and MBA from University of Illinois at Urbana-Champaign, and a Masters of Public Health from the University of Southern California Keck School of Medicine. Farva has an extensive background in consulting, marketing, research and legal fields. She works closely with TMAC to bring many of their high-quality algorithms onto Apervita’s platform.
Dr. Chad Rudnick, MD, FAAP is a board-certified pediatrician in Boca Raton, FL. He is the Medical Director of The Medical Algorithms Company. A proponent of incorporating medical technology into his practice, Dr. Rudnick uses telemedicine and medical algorithms from The Medical Algorithms Company in his daily practice to better serve his patients and their families. An accomplished medical writer, he maintains a popular pediatric blog, All Things Pediatric, and has written for numerous online and print publications including KevinMD.com.
John Svirbely, MD is a founder and Chief Medical Officer of The Medical Algorithms Company and the primary author of its medical algorithms. John is a co-founder of the Medical Algorithms Project and has developed its medical content for nearly 20 years. He has a BA degree from the Johns Hopkins University and his MD from the University of Maryland. He is a board-certified pathologist with a fellowship in medical microbiology and biomedical computing at Ohio State University. Currently he is in private practice in Cincinnati, Ohio. He has authored multiple books and articles on medical algorithms.
Note: This case study is fictional and based on actual events.