ESMO calls for oncology-specific safeguards in EU joint clinical assessments of medical and in vitro diagnostic devices in the new EU public consultation

The European Society for Medical Oncology (ESMO) has compiled a detailed response to the European Commission's public consultation draft regarding Implementing Regulation for Joint Clinical Assessments of medical and in vitro diagnostic devices.  The 4 key strategic priorities noted in the framework include systematic inclusion of oncology expertise, structured stakeholder involvement, proportional and feasible evidence requirements, and clear and consistent guidance on comparators and outcomes. 

To learn more and read the full submission, click here. 

National Institutes of Health launches research network to evaluate emerging cancer screening technologies

 The National Institutes of Health (NIH) has unveiled a clinical trials network focused on evaluating various cancer screening technologies.  This work is in support of Cancer Moonshot, "investigating how to identify cancers earlier, when they may be easier to treat."  

To read more about this research network, click here. 

Online tool predicts RFS and OS probabilities in patients with stage II melanoma

A new model created by Melanoma Institute Australia (MIA), further described and discussed in a recent issue of the Journal of Clinical Oncology, has been shown to "predict recurrence-free survival and overall survival in patients with a primary cutaneous melanoma considerably better" than what is described in cancer staging manuals.  Study authors further concluded that the MIA model can be used in daily practice without the need to conduct sentinel node biopsy, even for high-risk patients.  

To learn more about the MIA model, click here. 

Study mentioned: 

Varey AHR, Li I, El Sharouni M-A, et al. Predicting Recurrence-Free and Overall Survival for Patients With Stage II Melanoma: The MIA Calculator. JCO; Published online 5 February 2024. DOI: https://doi.org/10.1200/JCO.23.01020

Artificial intelligence for earlier detection of pancreatic cancer

A recent presentation at the ESMO (European Society of Medical Oncology) World Congress on Gastrointestinal Cancer, held in Lugano, Switzerland, July 1-4, 2020, indicates that artificial intelligence (AI) is gaining support for earlier detection of pancreatic cancer.  70-80% of pancreatic cancer patients are diagnosed at an advanced stage where treatment may no longer be effective, resulting in only a 6% survival rate 5 years after diagnosis.  The study, conducted on 1,378 pancreatic cancer patients between 15-99 years of age shows that for those under 60, the AI model "could predict who was at higher risk of pancreatic cancer up to 20 months before diagnosis."

To read more about this study, click here

Breast MRI associated with significantly higher rate of invasive cancer detection than digital breast tomosynthesis

A recent cross-sectional study with longitudinal follow-up on 1444 women undergoing breast cancer screening indicates that invasive cancer rate was considerable higher (11.8/1000) for breast MRI, compared to 4.8/1000 for digital breast tomosynthesis. While the authors of the study caution that further investigation of the correlation between screening methods and clinical outcome should be undertaken, the findings do support the notion that "improved screening methods for women with dense breasts are needed because of their increased risk of breast cancer and of failed early diagnosis by screening mammography."

To read more about this study, click here.

Source mentioned:   Comstock CE, Gatsonis C, Newstead GM, et al. Comparison of abbreviated breast MRI vs. digital breast tomosynthesis for breast cancer detection among women with dense breasts undergoing screening.  JAMA 2020;323(8):746-756. doi:10.1001/jama.2020.0572.

First baby born to cancer patienst from eggs matured in lab and frozen

The Department of Reproductive Medicine and Fertility Preservation at the Antoine Béclère University Hospital near Paris, France have "announced the birth of the first baby to be born to a cancer patient from an immature eff that was matured in the laboratory, frozen, then thawed and fertilized five years later."  According to the announcement, the 34-year old mother of the baby boy was infertile due to the chemotherapy she underwent for breast cancer.  Prior to beginning her cancer treatment, her immature eggs were removed and allowed to fully develop via in vitro maturation (IVM).  This study is believed to be the first successful pregnancy in cancer patients following IVM and vitrification.

To read more about this study, click here.

Artificial Intelligence speeds brain tumour diagnosis

A recent National Institutes of Health (NIH)-funded clinical trial of patients requiring brain surgery indicates how artificial intelligence (AI) is able to provide "neurosurgeons with valuable real-time information about what type of brain tumour is present, while the patient is still on the operating table."  In the joint study by researchers from NYU Langone Health and University of Michigan, Ann Arbor, the benefits of AI and a technique known as Stimulated Raman History (SRH) can provide real-time data and predictions related to a patient's brain tumour diagnosis.  AI overall performance in this study was 95% accurate (compared to 94% accuracy for conventional pathology).

To read more about this study, click here.

Source mentioned: Hollon TC, Pandian B, Adapa AR, Urias E, Save AV, Khalsa SS, et al. Near real-time intraoperative brain tumor diagnosis using stimulated Raman histology and deep neural networks. Nat Med. 2020 Jan 6. doi: 10.1038/s41591-019-0715-p [Epub ahead of print]

AI detects breast cancer as accurately as expert radiologists, study finds

Researchers in the United States and Britain recently reported that Google DeepMind, an artificial intelligence (AI) system, "proved as good as expert radiologists at detecting which women had breast cancer based on screening mammograms and showed promise at reducing errors."  According to the American Cancer Society, radiologists miss about 20% of breast cancers in mammograms; Google Deep Mind can reduce false positive results by 5.7%.

To read more about this study, click here.

Study mentioned: McKinney SM, Sieniek M, Godble V, Godwin J, Antropova H, Back T, et al. International evaluation of an AI system for breast cancer screening.  Nature, 2020 Jan; 577 (7788): 89-94.

Communication between cancer patients and healthcare professionals through digital media

Researchers representing the European Organization for Treatment and Research of Cancer (EORTC) have recently completed a study on the use of social media by cancer patients as a means of discussing the cancer journey with fellow peers.  According to study authors Daniel P. Oran and Eric J. Topol, "social media may be taken a step further to provide a new tool for patient-caregiver interaction that allows oncologists to learn their patients' true concerns."


To read more about this study, click here


Source mentioned: Oran DP, Topol EJ. The rise of the virtualist. Lancet 2019 Jul 6; 394(10192).

New trial alert: Mobile app postoperative home monitoring after enganced recovery oncologis surgery

A new trial sponsored by the Alberta Cancer Foundation and Alberta Health Services is recruiting participants in a new study seeking to determine whether the combined use of Enhanced Recovery After Surgery (ERAS) protocols and post-surgery following up via a mobile app improves patient satisfaction  as well as reducing the number of postoperative emergency room visits, thus decreasing healthcare costs.  Study participants requests are "women having mastectomy, breast reconstruction, and gynecological oncology procedures."


To learn more about this trial, click here.

Artificial Intelligence (AI) for breast cancer detection

A new study conducted at the Massachusetts Institute of Technology (MIT) lends support to the use of artificial intelligence (AI) to predict breast cancer risk in women.  The study, which involved more than 8,7000 mammogram images showed that the AI algorithm "placed almost one-third of women who developed breast cancer into the top 10% risk category...in contrast, the standard model put 18% of those women in the top 10%."  According to Arkadiusz Sitek, senior scientist at IBM Watson Health in Cambridge, Mass, these findings are not meant to suggest that AI will replace human doctors; rather "AI will serve as a radiologist's assistant, helping to improve efficiency and watch out for "errors and inconsistencies"


To read more about this study, click here

Artificial Intelligence to improve lung cancer screening

A new study conducted at the University of Pittsburgh has introduced a type of Artificial Intelligence (AI) to improve lung cancer screening.  According to study co-author Panayiotis Benos, vice chairman of computational and systems biology, CT scan data from high-risk patients was entered into "a machine learning algorithm - a form of artificial intelligence" to create a model that calculates the probability of cancer."  Upon comparison of the results from the model vs. a patient's diagnosis via traditional screening methods, "the model would have spared 30% of patients with benign nodules from further, unnecessary tests, without missing a single case of cancer."


To read more about this study, click here.


Study mentioned: Raghu VK, Zhao W, Pu J, Leader JK, Wang R, Herman J, Yuan JM, Benos PV, Wilson DO. Feasibility of lung cancer prediction from low-dose CT scan and smoking factors using causal models. Thorax 2019 Mar 12. doi: 10.1136/thoraxjnl-2018-212638 [Epub ahead of print]

Using artificial intelligence to classify lung cancer types and predict mutations

Researchers are working on training a computer program to read slides of tissue samples to diagnose two of the most common types of lung cancer with 97% accuracy. The program also learned to detect cancer-related genetic mutations in the samples just by analyzing the images of cancer tissue.

To read more about this research, click here.

Testing an interactive approach to promote exercise in young cancer survivors

A study at the St. Jude Children's Research Hospital created an interactive website designed to promote physical activity among children and adolescents who have completed treatment for cancer. According to preliminary results from a pilot study, the website may indeed help encourage them to get regularly exercise.

To read more about this study, click here.

Electric cap device offers hope to glioblastoma patients

A recent CTV news report introduced an electric cap-like device for patients with glioblastoma, an aggressive brain cancer with a 5-year survival rate of only 5%.  Known as Optune, the device, which is worn by patients 18 hours per day, "emits a low-intensity electromagnetic field to stop or slow cancer cells from dividing."  Regular use of the device has increased life expectancy by 4 months, however it has also increased the survival rate after 5 years to 13%.

To read more about this news story, click here.

Artificial intelligence as a possible partner in breast cancer care

New research conducted at the Massachusetts General Hospital suggests that artificial intelligence can help doctors identify high-risk breast lesions that could manifest into cancer. According to study author Dr. Manisha Bahi, the machine learning test involved 1,000 women with high-risk breast lesions, identifying 37 of 38 lesions correctly. 

To read more about this study, click here.

Amy Reed, physician and patient who “moved mountains” to end widespread use of power morcellation, dies at 44

“I always wanted to be a doctor when I was little,” Reed said in 2015. “I wanted to go into medicine and be a doctor and fix things, and cure the world.”


Reed’s dream came true, albeit not in the way she envisioned.


Reed, a Pennsylvania native, died May 24 from complications stemming from disseminated uterine cancer. She was 44.


Read this true story of how the use of power morcellators should not be used for hysterectomies or fibroid removal.

WHO list of priority medical devices for cancer management

Have you checked the new priority list of medical devices for cancer management? This list also describes for six types of cancer: breast, cervical, colorectal, leukemia, lung and prostate.

Rationale for anti-OX40 cancer immunotherapy

In the January 2016 edition of the EJC, authors from the Gustave Roussy Cancer Centre, Villejuif, France present their rationale for anti-OX40 immunotherapy for the treatment of cancer. Lead author, Sandrine Aspelaugh, explains why blocking the OX40 molecule could become an important new approach in immunotherapy in the EJC’s January podcast. Read more here.

Using sound waves to detect rare cancer cells

Cancer cells often break free from their original locations and circulate through the bloodstream, allowing them to form new tumors elsewhere in the body. Detecting these cells could give doctors a new way to predict whether patients’ tumors will metastasize, or monitor how they are responding to treatment, but finding these extremely rare cells has proven challenging because there might be only one to 10 such cells in a 1-milliliter sample of a patient’s blood. A team of engineers from MIT, Penn State University, and Carnegie Mellon University is developing a novel way to isolate these cells: using sound waves to separate them from blood cells. Read more here.