Breaking Research News from sources other than Breastcancer.org

Lumpie · May 2020

Patient Age, Use of Checkpoint Inhibitors in Cancer Linked to COVID-19 Severity

A study by researchers from the Memorial Sloan Kettering Cancer Center estimated that 40% of the 423 patients with cancer who were symptomatic for SARS-CoV-2 were hospitalized for COVID-19.1 Looking at these patients, the researchers identified several characteristics that conferred risk.

A multivariable analysis showed that patients 65 years or older and those who had been treated with immune checkpoint inhibitors (ICIs) within 90 days of admittance had a higher likelihood for hospitalization and severe disease. ***In contrast, receipt of chemotherapy within 30 days and prior major surgery did not increase the risk of developing the virus.*** {emphasis added}

These data were published online on medRxiv.org. The data were not peer-reviewed, and the results of the study should be considered preliminary.

"Until more extensive studies are available, it is prudent not to alter treatment decisions, but consider SARS-CoV-2 testing for patients initiating or continuing treatment with ICIs irrespective of symptoms."

https://www.cancertherapyadvisor.com/home/cancer-topics/general-oncology/covid19-coronavirus-severity-cancer-patient-age-checkpoint-inhibitor-use-link/?utm_source=newsletter&utm_medium=email&utm_campaign=cta-update-hay-20200530&cpn=&hmSubId=nIej-0ANyLQ1&hmEmail=02k_9hvA1kiS6nmG9LnGT5WH-O6RhZf90&NID=&email_hash=f6f19b3bf12938acdd2c69cb86958025&dl=0&mpweb=1323-93466-6515878

Robilotti EV, Babady NE, Mead PA, et al. Determinants of severity in cancer patients with COVID-19 illness [preprint published online May 8, 2020]. medRxiv. doi: 10.1101/2020.05.04.20086322

Salamandra · May 2020

Thank you for sharing that Lumpie! it Is so good to have some studies/data about risks and cancer. And of course we owe gratitude for that information to our sisters and brothers who went into this unknown first

Lumpie · June 2020

Study Challenges the Association Between Surgical Margin Size and Breast Cancer Recurrence

Surgical margin size did not appear to be associated with locoregional recurrence for patients with breast cancer who underwent breast-conserving surgery and *neoadjuvant* chemotherapy, a retrospective, single-institution study found. The results were recently reported in BMC Cancer.

Patients with breast cancer who received neoadjuvant chemotherapy between January 2008 and April 2018 were identified from an institutional database.

https://www.oncologynurseadvisor.com/home/cancer-types/breast-cancer/breast-cancer-surgical-margin-study-challenges-recurrence/?utm_source=newsletter&utm_medium=email&utm_campaign=ona-update-hay-20200603&cpn=&hmSubId=nIej-0ANyLQ1&hmEmail=02k_9hvA1kiS6nmG9LnGT5WH-O6RhZf90&NID=&email_hash=f6f19b3bf12938acdd2c69cb86958025&mpweb=1323-94459-6515878

Lin J, Lin K, Wang Y, Huang L, Chen SL, and Chen D. Association of surgical margins with local recurrence in patients undergoing breast-conserving surgery after neoadjuvant chemotherapy [published online May 20, 2020]. BMC Cancer. doi: 10.1186/s12885-020-06955-6

Lumpie · June 2020

Disconnect Between FDA Approval of Oncology Drugs and Publication of Results of Registration Trials

During 2000 to 2019, no peer-reviewed publication of registration trial results was available for nearly half of oncology drugs granted accelerated approval by the US Food and Drug Administration (FDA) at the time of authorization, according to findings of a retrospective study released as part of the ASCO20 Virtual Scientific Program.1

No systematic investigations have evaluated the timing of oncology drug registration trial publication relative to the approval of these drugs by the FDA.

Although package inserts include data from these studies, "FDA labels can be highly variable in the amount of information that they provide, and they rarely contain the information that is found in published manuscripts, in particular details such as the study protocol [and] inclusion and exclusion criteria,"

In their concluding remarks, the study authors noted that because "trial publications help with adoption of new treatments and mitigation of adverse effects … efforts are needed to ensure trial results are published in a timely manner."

https://www.cancertherapyadvisor.com/home/news/conference-coverage/american-society-of-clinical-oncology-asco/asco-2020/fda-approval-oncology-cancer-drugs-disconnect-between-publication-results-trial/?utm_source=newsletter&utm_medium=email&utm_campaign=cta-update-hay-20200603&cpn=&hmSubId=nIej-0ANyLQ1&hmEmail=02k_9hvA1kiS6nmG9LnGT5WH-O6RhZf90&NID=&email_hash=f6f19b3bf12938acdd2c69cb86958025&dl=0&mpweb=1323-94570-6515878

Khaki AR, Desai A, Schoen MW, et al. Timing of US Food and Drug Administration (FDA) cancer drug approvals relative to publication of clinical trial results. Presented at: ASCO20 Virtual Scientific Program. J Clin Oncol. 2020;38(suppl):abstr 2071.
HemOnc.org. https://www.hemonc.org/wiki/Main_Page. Accessed May 27, 2020.

Lexica · June 2020

From the PALLAS trial: Ibrance for early stage hormone receptor positive breast cancer failed to meet the primary endpoint.

https://www.benzinga.com/news/20/05/16143680/pfize...

Lumpie · June 2020

Machine Learning Algorithm Predicts Financial Burden Due To Cancer Treatment

A machine-learning algorithm was able to predict the rate of financial stress on patients who underwent treatment for their breast cancer, according to a retrospective survey and algorithm-modeling study. These findings were presented during the ASCO 2020 Virtual Scientific Program.

The machine learning algorithm predicted financial burden with a high accuracy (83%), sensitivity (81%), and specificity (82%), and area under the receiver operating curve (0.82)

The study authors concluded that their machine learning model could accurately predict financial difficulties due to treatment of breast cancer. These predictions may aide in the decision-making process and that with careful planning, financial distress may be avoided. As financial toxicity is associated with poorer clinical outcomes, avoiding this stressor would ultimately lead to better quality of care.

https://www.oncologynurseadvisor.com/home/headlines/conference-coverage/asco-2020/machine-learning-algorithm-predicts-financial-burden-due-to-cancer-treatment/

Sidey-Gibbons C, Asaad M, Pfob A, Boukovalas S, Lin YL, Offodile. Machine learning algorithms to predict financial toxicity associated with breast cancer treatment. Presented at: ASCO20 Virtual Scientific Program. J Clin Oncol. 2020;38(suppl):abstr 2047.

Lumpie · June 2020

CMS to make some pandemic telehealth waivers permanent

CMS Administrator Seema Verma said use of telehealth has grown dramatically during the pandemic, and some provisions that temporarily expanded access to telehealth during the pandemic will be made permanent. She said the agency is working on rulemaking now.

https://www.beckershospitalreview.com/telehealth/some-temporary-telehealth-provisions-will-become-permanent-cms-chief-says.html

FDA: Some COVID-19 policies could be here to stay

FDA Commissioner Stephen Hahn said the agency is considering permanently implementing some of the policies and processes adopted in response to the COVID-19 pandemic. Most of the changes "represent an acceleration of where we were headed before," including increased use of telemedicine in clinical trials, support for decentralized clinical studies and work on laboratory-developed tests, Hahn said.

https://www.raps.org/news-and-articles/news-articles/2020/6/hahn-fda-will-make-some-changes-amid-covid-19-perm

BevJen · June 2020

Interesting article on how cancers mutate to get around targeted treatments --

https://scienmag.com/revealed-how-cancer-develops-...

Bliss58 · June 2020

BevJen, thanks for sharing that article on bc cell mutation and resistance. Very interesting.

Lumpie · June 2020

New Clue to Anti-PD-L1 Activity in Breast Cancer?

— Survival benefit with durvalumab in patients with PDL1 copy number alteration

A novel biomarker identified a large subgroup of metastatic breast cancer patients who benefited from an immune checkpoint inhibitor, according to an exploratory analysis of a prospective clinical trial.

Almost a fourth of patients with no identified actionable mutations had copy number alteration (CNA) in the PD-L1 gene. Patients without PD-L1 CNA had a median progression-free survival (PFS) of 9 months when treated with the PD-L1 inhibitor durvalumab (Imfinzi), whereas median PFS had yet to be reached in patients whose tumors had copy number gain (three or four copies) or amplification (more than four).

"This exploratory translational analysis suggested a higher efficacy of durvalumab as maintenance treatment for patients with PD-L1 copy gain or amplification," Bachelot said in a statement. "PD-L1 copy number alteration could be an important predictive marker for PD-L1 inhibitor efficacy. If confirmed in larger series, this could have important implications for the development of immunotherapy in patients with metastatic breast cancer, enabling us to better identify patients that are sensitive to PD-L1 inhibitors than current testing for PD-L1 positivity on immune cells."

Link to the clinical trial:

https://clinicaltrials.gov/ct2/show/NCT02299999

https://www.medpagetoday.com/meetingcoverage/additionalmeetings/86683?xid=nl_mpt_SROBGYN_2020-05-30&eun=g1278169d0r&utm_source=Sailthru&utm_medium=email&utm_campaign=ObGynUpdate_053020&utm_term=NL_Spec_OBGYN_Update_Active

Primary Source: ESMO Breast Cancer Conference

Source Reference: Bachelot T, et al "PDL1/CD274 gain/amplification as a predictive marker of checkpoint blockade inhibitor efficacy in metastatic breast cancer: Exploratory analysis of the SAFIR02-Immuno randomized phase II trial" ESMO Breast Cancer Conference 2020; Abstract 128O.

Lumpie · June 2020

TRAIN-2 Highlights Questions Around the Use of Anthracycline-Based Neoadjuvant Chemotherapy in HER2-Positive Breast Cancer

Long-term follow-up of a phase 3 study showed that anthracycline-based neoadjuvant chemotherapy did not improve event-free survival (EFS) or overall survival (OS) in patients with HER2-positive, nonmetastatic breast cancer compared with a taxane-platinum regimen when trastuzumab and pertuzumab were coadministered with chemotherapy. These findings were presented during the ASCO20 Virtual Scientific Program.

At a median follow-up of 19 months, a previously published analysis of results from 418 patients in this trial showed no difference in the primary study end point of pathologic complete response (pCR) rate when patients treated with an anthracycline (67%) and without an anthracycline (68%) were compared (P =.95).In addition, a significantly higher rate of at least grade 3 febrile neutropenia were observed in the anthracycline-containing arm (10%) compared with the anthracycline-free arm (1%; P =.0001).

https://www.cancertherapyadvisor.com/home/news/conference-coverage/american-society-of-clinical-oncology-asco/asco-2020/breast-cancer-train2-highlights-questions-around-use-anthracycline-chemo/?utm_source=newsletter&utm_medium=email&utm_campaign=cta-update-hay-20200609&cpn=&hmSubId=nIej-0ANyLQ1&hmEmail=02k_9hvA1kiS6nmG9LnGT5WH-O6RhZf90&NID=&email_hash=f6f19b3bf12938acdd2c69cb86958025&dl=0&mpweb=1323-95171-6515878

References

Van der Voort A, van Ramshorst MS, van Werkhoven ED, et al. Three-year follow-up of neoadjuvant chemotherapy with or without anthracyclines in the presence of dual HER2-blockade for HER2-positive breast cancer (TRAIN-2): A randomized phase III trial. ASCO20 Virtual Scientific Program. J Clin Oncol. 2020;38(suppl):abstr 501.
van Ramshorst MS, van der Voort A, van Werkhoven ED, et al. Neoadjuvant chemotherapy with or without anthracyclines in the presence of dual HER2 blockade for HER2-positive breast cancer (TRAIN-2): A multicentre, open-label, randomised, phase 3 trial. Lancet Oncol. 2018;19:1630-1640.

Lumpie · June 2020

Cancer Care Costs in the United States Are Projected to Exceed $245 Billion by 2030

The national healthcare bill for cancer will exceed $245 billion a year by 2030, a 30% increase from 2015. (American Association for Cancer Research)

The national cancer-attributable costs in the United States are projected to increase by over 30 percent from 2015 to 2030, corresponding to a total cost of over $245 billion, according to a study published in Cancer Epidemiology, Biomarkers & Prevention, a journal of the American Association for Cancer Research.

https://www.aacr.org/about-the-aacr/newsroom/news-...

https://cebp.aacrjournals.org/content/early/2020/0...

DOI: 10.1158/1055-9965.EPI-19-1534

Lumpie · June 2020

Has the Time for At-Home Cancer Care Finally Come?

"...patients have routinely received home treatments using infusion pumps for other conditions, including autoimmune diseases and diabetes. "We asked why this couldn't be a real option for cancer patients, too," ..."The idea of hospital-at-home has been around for years and already has a successful track record."

In November 2019, his team got to work creating a model so doctors could prescribe 13 drugs for {cancers for administration} at home.

When the program was launched in February 2020, 40 patients signed up. By the beginning of June {2020}, the program had more than 400 patients. "It's skyrocketed," he said. "We scaled that quickly because it became clear that we needed to decrease density in the hospital and infusion suites to have capacity for COVID-19."

https://www.cancertherapyadvisor.com/home/cancer-t...

Reference

Lüthi F, Fucina N, Divorne N, et al. Home care—a safe and attractive alternative to inpatient administration of intensive chemotherapies. Support Care Cancer. 2012;20:575-581.

Lumpie · June 2020

High Medical Costs Associated With Metastatic Breast Cancer

In this study, the authors used 2003–2014 North Carolina cancer registry data linked with administrative claims to develop an algorithm for identifying patients with breast cancer who progressed to metastatic disease. Medical costs due to metastatic breast cancer were estimated by age group and by phase of care. Monthly costs were significantly higher for women with metastatic breast cancer compared with earlier-stage breast cancer and patients without cancer for all age groups and phases of treatment except for initial treatment among women with stage III disease at diagnosis. The highest expected costs were for women aged 18 to 44 during the continuing phase of care, totaling over $200,000.

These findings highlight the importance of determining whether the excess costs among younger women and during the continuing and terminal phases of treatment provide high value for these women.

https://www.practiceupdate.com/journalscan/68839/6...

https://link.springer.com/article/10.1007/s10549-0...

DOI https://doi.org/10.1007/s10549-020-05654-x

(There is a discussion about cost of care by Lillie D Shockney. It seems to focus on the merits of limiting expensive care in order not to bankrupt the patient rather than addressing why we allow medical care in the US to bankrupt patients in the first place.}

Lumpie · June 2020

FDA Approves Pfizer's Oncology Supportive Care Biosimilar, NYVEPRIA™ (pegfilgrastim-apgf)

June 11, 2020 NEW YORK--(BUSINESS WIRE)-- Pfizer Inc. (NYSE: PFE) today announced the United States (U.S.) Food and Drug Administration (FDA) has approved NYVEPRIA™ (pegfilgrastim-apgf), a biosimilar to Neulasta^® (pegfilgrastim).¹ NYVEPRIA is indicated to decrease the incidence of infection, as manifested by febrile neutropenia, in patients with non-myeloid malignancies receiving myelosuppressive anti-cancer drugs associated with a clinically significant incidence of febrile neutropenia.

https://investors.pfizer.com/investor-news/press-r...

Lumpie · June 2020

New Protocol on Breast Cancer and Breastfeeding

New Rochelle, NY, June 10, 2020—Managing women with breast cancer who are breastfeeding is a complex issue. The Academy of Breastfeeding Medicine presents new recommendations in the peer-reviewed journal Breastfeeding Medicine. Click here to read the article now.

"The aim of this new protocol is to guide clinicians in the delivery of optimal care of breastfeeding women as it relates to breast cancer, from screening to diagnosis, treatment, and survivorship," state coauthors Helen Johnson, MD and Katrina Mitchell, MD.

It addresses the spectrum of care, including oncologic breast surgery, chemotherapy, and adjuvant and endocrine therapy. A section on breastfeeding women who have a previous history of breast cancer is included.

Arthur I. Eidelman, MD, Editor-in-Chief of Breastfeeding Medicine, states: "This protocol is a guide for mothers who are undergoing diagnosis and treatment for breast cancer. It emphasizes that they do not have to categorically give up on their nurturing role as breastfeeding moms."

Breast cancer is the most common malignancy in women worldwide. One in 20 women will develop breast cancer in their lifetime.

https://home.liebertpub.com/news/new-protocol-on-b...

https://www.liebertpub.com/doi/10.1089/bfm.2020.29...

Published Online:9 Jun 2020 https://doi.org/10.1089/bfm.2020.29157.hmj

Anonymous · June 2020

City of Hope - Ultrasound to a kill Cancer Cells (apologies if this has been posted already)

https://www.cityofhope.org/breakthroughs/using-ultrasound-to-kill-cancer-cells

santabarbarian · June 2020

Olma the links do not work

BlueGirlRedState · June 2020

Olma61 - the links did not work for me either. I knew ultrasound was used in detection, but had not heard of using for treatment, so asked Dr. Google. Maybe there is hope

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4362523/

https://www.webmd.com/cancer/news/20200110/targeted-ultrasound-destroys-cancer-without-harming-healthy-cells-study

Lumpie · June 2020

Live stream: Chasing Cancer

Stephen M. Hahn, U.S. Food and Drug Administration commissioner, will lay out his agenda for the FDA and discuss critical steps the government is taking to approve innovative, life-saving drugs, therapies, and clinical trials for COVID-19 and cancer. As an oncologist, Hahn has spent his career dedicated to advancing cancer treatment. James P. Allison, the 2018 Nobel Prize winner in Medicine for his immunotherapies at MD Anderson Cancer Center, will discuss the next steps in his ground breaking research, one of the most important advances in cancer treatment in 100 years. We'll also focus on DNA and genetic testing, groundbreaking immunotherapies and drugs that topline researchers hope will combat the deadliest cancers.

In a segment presented by Pfizer, Andy Schmeltz, global president & general manager of Pfizer's Oncology division will discuss the challenges, barriers, and inequities within the current healthcare system, and what we can do to fix it.

Join us on Wednesday, June 17 at 10:30 a.m. ET.

Stream here: wapo.st/chasingcancerjune

https://chasingcancerjune.splashthat.com/?utm_medi...

Anonymous · June 2020

Hi ladies, sorry about the broken link I edited the post just now to fix it and here is the correct link to the City of Hope article:

https://www.cityofhope.org/breakthroughs/using-ultrasound-to-kill-cancer-cells

Good to see those other links too!

BevJen · June 2020

Lumpie -

Thanks for posting the Post talk -- that sounds like a good one. And they've got two good people -- I've heard interviews with Allison before and they were fascinating.

Lumpie · June 2020

Study Finds Wide Variation in the Natural History of Untreated ER-Positive, HER2-Negative Invasive Breast Cancer Tumors

Results of a retrospective study evaluating multiple characteristics of a cohort of individuals with untreated estrogen receptor-positive, HER2-negative invasive breast cancers showed a broad range of tumor growth velocities across patients. This study examined the in-vivo tumor growth kinetics for patients presenting with "missed" ER-positive, HER2-negative invasive breast cancer that had been present, but unidentified, on 1 or more previous serial screening mammographic images performed at least 6 months prior to the diagnosis of breast cancer. Changes in tumor volume over time (ie, tumor growth velocity) and tumor doubling time were estimated for these tumors.

The study authors noted that these results "demonstrated a variation of in-vivo growth kinetics in an untreated subset of breast cancers and found that the volume change over time could not be predicted."

They further commented that these results show that more difficult-to-measure factors such as host immune response, tumor microenvironment, and molecular heterogeneity may play a larger role than solely tumor subtype.

https://www.cancertherapyadvisor.com/home/cancer-t...

Reference

Rojas KE, M D-M, Rojas M, et al. The natural history of untreated estrogen receptor-positive, Her2-negative invasive breast cancer. Breast Cancer Res Treat [published online May 12, 2020]. doi: 10.1007/s10549-020-05666-7

BlueGirlRedState · June 2020

The Chasing Cancer Postponed until June 24th. IF you register, they will send reminder https://chasingcancerjune24.splashthat.com/

BSandra · June 2020

Probably something about "driving" genes: http://news.mit.edu/2020/counting-your-antigens-cancer-immunotherapy-0602. One can see targeted/immunotherapy treatment revolution is not far away...

JoynerL · June 2020

BSandra, this is very exciting! That "grad student" must be something! Thanks for posting.

JoynerL · June 2020

I'm not sure how I found this subscription or who recommended it (probably someone on this string), but it is excellent. I'm sorry if it's fuzzy. It seems to originate from "Practice Update":

<img 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

JoynerL · June 2020

Just saw this on OBR:

https://news.nd.edu/news/common-cholesterol-drugs-could-slow-spread-of-breast-cancer-to-brain/

debbew · June 2020

'Unbelievably Exciting' Results in Rare Type of Breast Cancer

Metaplastic breast cancer (MpBC) is a rare form of triple-negative breast cancer (TNBC), accounting for fewer than 1% of all breast cancers, but it is very aggressive and responds poorly to chemotherapy. So new results with a combination of immunotherapies that resulted in significant tumor shrinkage and survival topping 2 years have led to some excitement, even though the results were seen in only 3 of 17 women who were treated...

There was one complete response and two partial responses with "very little tumor burden left. That gives us the hope that maybe there is a chance for cure in these three patients..."

https://www.medscape.com/viewarticle/932634

Bliss58 · June 2020

It looks like Chasing Cancer with WaPo is an ongoing series? I missed the one June 17, best friend's 60th, but see the one on June 24 is a different topic. So I'm wondering, was the previous one postponed, didn't happen or I just missed it?

Joyner, thanks for that OBR share. Interesting research for another potential benefit of my dr. putting me on a statin.