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Reply To the Letter to the Editor by Frugé et al

Daan A.C. Lanser, Anne-Marie C. Dingemans, Ron H.J. Mathijssen, and G.D. Marijn Veerman

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Validation of the PREDICT Prognostication Tool in US Patients With Breast Cancer

Nickolas Stabellini, Lifen Cao, Christopher W. Towe, Megan E. Miller, Artur H. Sousa-Santos, Amanda L. Amin, and Alberto J. Montero

Background: PREDICT is an online prognostication tool derived from breast cancer registry information on approximately 6,000 women treated in the United Kingdom that estimates the postsurgical treatment benefit of surgery alone, chemotherapy, trastuzumab, endocrine therapy, and/or adjuvant bisphosphonates in early-stage breast cancer. Our aim was to validate the PREDICT algorithm in predicting 5- and 10-year overall survival (OS) probabilities using real-world outcomes among US patients with breast cancer. Methods: A retrospective study was performed including women diagnosed with unilateral breast cancer in 2004 through 2012. Women with primary unilateral invasive breast cancer were included. Patients with bilateral or metastatic breast cancer, no breast surgery, or missing critical clinical information were excluded. Prognostic scores from PREDICT were calculated and external validity was approached by assessing statistical discrimination through area under time-dependent receiver-operator curves (AUC) and comparing the predicted survival to the observed OS in relevant subgroups. Results: We included 708,652 women, with a median age of 58 years. Most patients were White (85.4%), non-Hispanic (88.4%), and diagnosed with estrogen receptor–positive breast cancer (79.6%). Approximately 50% of patients received adjuvant chemotherapy, 67% received adjuvant endocrine therapy, 60% underwent a partial mastectomy, and 59% had 1 to 5 axillary sentinel nodes removed. Median follow-up time was 97.7 months. The population’s 5- and 10-year OS were 89.7% and 78.7%, respectively. Estimated 5- and 10-year median survival with PREDICT were 88.3% and 73.8%, and an AUC of 0.77 and 0.76, respectively. PREDICT performed most poorly in patients with high Charlson-Deyo comorbidity scores (2–3), where PREDICT overestimated OS. Sensitivity analysis by year of diagnosis and HER2 status showed similar results. Conclusions: In this prognostic study utilizing the National Cancer Database, the PREDICT tool accurately predicted 5- and 10-year OS in a contemporary and diverse population of US patients with nonmetastatic breast cancer.

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Volume 21 (2023): Issue 9 (Sep 2023)

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Biomarker Testing, Treatment, and Outcomes in Patients With Advanced/Metastatic Non–Small Cell Lung Cancer Using a Real-World Database

Naleen Raj Bhandari, Lisa M. Hess, Dan He, and Patrick Peterson

Background: Little is known about the impact of up-front biomarker testing on long-term outcomes in patients with advanced or metastatic non–small cell lung cancer (a/mNSCLC). This study compared overall survival (OS) by biomarker testing status and by receipt of guideline-concordant therapy in a large real-world cohort of patients with a/mNSCLC in the United States. Patients and Methods: This retrospective study used an a/mNSCLC database derived from real-world electronic healthcare records. Patients diagnosed with nonsquamous a/mNSCLC who initiated first-line therapy on or after January 1, 2015, were included. We describe the testing of patients for actionable biomarkers and whether they subsequently received guideline-recommended first-line treatment. OS was defined as the number of months from the initiation of first-line therapy to the date of death or end of follow-up, and was described using Kaplan-Meier analysis. Multivariable Cox proportional hazard modeling was conducted to compare OS between groups adjusting for baseline covariates; adjusted hazard ratios (HRs) were reported. Results: A total of 21,572 patients with a median age of 69 years (IQR, 61–76 years) and follow-up of 9.5 months (IQR, 3.5–21.5 months) were included. Among patients in the database, 88% had a record of receiving testing for at least 1 biomarker at any time, and 69% of these patients received testing before or at the start of first-line treatment. The adjusted hazard of death was 30% higher in patients who never (vs ever) received biomarker testing in the database (HR, 1.30; 95% CI, 1.24–1.37), and 12% higher in patients who did not receive (vs did receive) biomarker testing before or at the start of first-line treatment (HR, 1.12; 95% CI, 1.08–1.16). The adjusted hazard of death was 25% higher in patients who did not receive guideline-concordant first-line treatment (vs those who did) after having a biomarker-positive disease (HR, 1.25; 95% CI, 1.13–1.40). Conclusions: Findings suggest that receipt of first-line treatment that is concordant with biomarker testing results and treatment guidelines is associated with improved survival outcomes in patients with a/mNSCLC in the United States.

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Hidden Disparities: How Language Influences Patients’ Access to Cancer Care

Debbie W. Chen, Mousumi Banerjee, Xin He, Lesley Miranda, Maya Watanabe, Christine M. Veenstra, and Megan R. Haymart

Background: Patients with limited English proficiency, a vulnerable patient population, remain understudied in the literature addressing cancer disparities. Although it is well documented that language discordance between patients and physicians negatively impacts the quality of patient care, little is known about how patients’ preferred spoken language impacts their access to cancer care. Patients and Methods: Between November 2021 and June 2022, we conducted an audit study of 144 hospitals located across 12 demographically diverse states. Using a standardized script, trained investigators assigned to the roles of English-speaking, Spanish-speaking, and Mandarin-speaking patients called the hospital general information telephone line seeking to access care for 3 cancer types that disproportionately impact Hispanic and Asian populations (colon, lung, and thyroid cancer). Primary outcome was whether the simulated patient caller was provided with the next steps to access cancer care, defined as clinic number or clinic transfer. We used chi-square tests and logistic regression analysis to test for associations between the primary outcome and language type, region type, hospital teaching status, and cancer care requested. We used multivariable logistic regression analysis to determine factors associated with simulated patient callers being provided the next steps. Results: Of the 1,296 calls, 52.9% (n=686) resulted in simulated patient callers being provided next steps to access cancer care. Simulated non–English-speaking (vs English-speaking) patient callers were less likely to be provided with the next steps (Mandarin, 27.5%; Spanish, 37.7%; English, 93.5%; P<.001). Multivariable logistic regression found significant associations of the primary outcome with language spoken (Mandarin: odds ratio [OR], 0.02 [95% CI, 0.01–0.04] and Spanish: OR, 0.04 [95% CI, 0.02–0.06] vs English) and hospital teaching status (nonteaching: OR, 0.43 [95% CI, 0.32–0.56] vs teaching). Conclusions: Linguistic disparities exist in access to cancer care for non–English-speaking patients, emphasizing the need for focused interventions to mitigate systems-level communication barriers.

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Highlights of the NCCN Oncology Research Program

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Impact of Muscle Measures on Outcome in Patients Receiving Endocrine Therapy for Metastatic Breast Cancer: Analysis of ECOG-ACRIN E2112

Tarah J. Ballinger, Helga S. Marques, Gloria Xue, Richard Hoffman, Constantine Gatsonis, Fengmin Zhao, Kathy D. Miller, Joseph Sparano, and Roisin M. Connolly

Background: Observational data investigating the relationship between body habitus and outcomes in breast cancer have been variable and inconsistent, largely centered in the curative setting and focused on weight-based metrics. This study evaluated the impact of muscle measures on outcomes in patients with metastatic breast cancer receiving endocrine-based therapy. Methods: Baseline CT scans were collected from ECOG-ACRIN E2112, a randomized phase III placebo-controlled study of exemestane with or without entinostat. A CT cross-sectional image at the L3 level was extracted to obtain skeletal muscle mass and attenuation. Low muscle mass (LMM) was defined as skeletal muscle index <41 cm2/m2 and low muscle attenuation (LMA) as muscle density <25 HU or <33 HU if overweight/obese by body mass index (BMI). Multivariable Cox proportional hazard models determined the association between LMM or LMA and progression-free survival (PFS) and overall survival (OS). Correlations between LMM, LMA, and patient-reported outcomes were determined using 2-sample t tests. Results: Analyzable CT scans and follow-up data were available for 540 of 608 patients. LMM was present in 39% (n=212) of patients and LMA in 56% (n=301). Those with LMA were more likely to have obesity and worse performance status. LMM was not associated with survival (PFS hazard ratio [HR]: 1.13, P=.23; OS HR: 1.05, P=.68), nor was LMA (PFS HR: 1.01, P=.93; OS HR: 1.00, P=.99). BMI was not associated with survival. LMA, but not LMM, was associated with increased frequency of patient-reported muscle aches. Conclusions: Both low muscle mass and density are prevalent in patients with hormone receptor–positive metastatic breast cancer. Muscle measures correlated with obesity and performance status; however, neither muscle mass nor attenuation were associated with prognosis. Further work is needed to refine body composition measurements and select optimal cutoffs with meaningful endpoints in specific breast cancer populations, particularly those living with metastatic disease.

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Mesothelioma: Peritoneal, Version 2.2023, NCCN Clinical Practice Guidelines in Oncology

David S. Ettinger, Douglas E. Wood, James Stevenson, Dara L. Aisner, Wallace Akerley, Jessica R. Bauman, Ankit Bharat, Debora S. Bruno, Joe Y. Chang, Lucian R. Chirieac, Malcolm DeCamp, Thomas J. Dilling, Jonathan Dowell, Gregory A. Durm, Scott Gettinger, Travis E. Grotz, Matthew A. Gubens, Aparna Hegde, Rudy P. Lackner, Michael Lanuti, Jules Lin, Billy W. Loo Jr, Christine M. Lovly, Fabien Maldonado, Erminia Massarelli, Daniel Morgensztern, Trey C. Mullikin, Thomas Ng, Gregory A. Otterson, Sandip P. Patel, Tejas Patil, Patricio M. Polanco, Gregory J. Riely, Jonathan Riess, Theresa A. Shapiro, Aditi P. Singh, Alda Tam, Tawee Tanvetyanon, Jane Yanagawa, Stephen C. Yang, Edwin Yau, Kristina M. Gregory, and Miranda Hughes

Mesothelioma is a rare cancer originating in mesothelial surfaces of the peritoneum, pleura, and other sites. These NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) focus on peritoneal mesothelioma (PeM). The NCCN Guidelines for PeM provide recommendations for workup, diagnosis, and treatment of primary as well as previously treated PeM. The diagnosis of PeM may be delayed because PeM mimics other diseases and conditions and because the disease is so rare. The pathology section was recently updated to include new information about markers used to identify mesothelioma, which is difficult to diagnose. The term “malignant” is no longer used to classify mesotheliomas, because all mesotheliomas are now defined as malignant.

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NCCN Guidelines® Insights: Breast Cancer Screening and Diagnosis, Version 1.2023

Featured Updates to the NCCN Guidelines

Therese B. Bevers, Bethany L. Niell, Jennifer L. Baker, Debbie L. Bennett, Ermelinda Bonaccio, Melissa S. Camp, Sona Chikarmane, Emily F. Conant, Mohammad Eghtedari, Meghan R. Flanagan, Jeffrey Hawley, Mark Helvie, Linda Hodgkiss, Tamarya L. Hoyt, Jennifer Ivanovich, Maxine S. Jochelson, Swati Kulkarni, Rachael B. Lancaster, Caitlin Mauer, Jessica Maxwell, Bhavika K. Patel, Mark Pearlman, Liane Philpotts, Donna Plecha, Jennifer K. Plichta, Shadi Shakeri, Mary Lou Smith, Clarie L. Streibert, Roberta M. Strigel, Lusine Tumyan, Nicole S. Winkler, Dulcy E. Wolverton, Mary Anne Bergman, Rashmi Kumar, and Katie Stehman

The NCCN Guidelines for Breast Cancer Screening and Diagnosis provide health care providers with a practical, consistent framework for screening and evaluating a spectrum of clinical presentations and breast lesions. The NCCN Breast Cancer Screening and Diagnosis Panel is composed of a multidisciplinary team of experts in the field, including representation from medical oncology, gynecologic oncology, surgical oncology, internal medicine, family practice, preventive medicine, pathology, diagnostic and interventional radiology, as well as patient advocacy. The NCCN Breast Cancer Screening and Diagnosis Panel meets at least annually to review emerging data and comments from reviewers within their institutions to guide updates to existing recommendations. These NCCN Guidelines Insights summarize the panel’s decision-making and discussion surrounding the most recent updates to the guideline’s screening recommendations.

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