Author
Jeremy J. Erasmus
Other affiliations: Harvard University, University of Texas Health Science Center at Houston
Bio: Jeremy J. Erasmus is an academic researcher from University of Texas MD Anderson Cancer Center. The author has contributed to research in topics: Lung cancer & Positron emission tomography. The author has an hindex of 41, co-authored 133 publications receiving 8456 citations. Previous affiliations of Jeremy J. Erasmus include Harvard University & University of Texas Health Science Center at Houston.
Papers published on a yearly basis
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Imperial College London1, University of Barcelona2, Keio University3, University of Duisburg-Essen4, Queen's University5, Peter MacCallum Cancer Centre6, University of Michigan7, University of São Paulo8, Yale University9, Northern General Hospital10, University of Caen Lower Normandy11, Fred Hutchinson Cancer Research Center12, University of Oxford13, Memorial Sloan Kettering Cancer Center14, University of Sydney15, Sungkyunkwan University16, Seoul National University17, Kyorin University18, University of Copenhagen19, Nippon Medical School20, Katholieke Universiteit Leuven21, University of Texas MD Anderson Cancer Center22, University of Antwerp23, Hyogo College of Medicine24, University of Western Australia25, Glenfield Hospital26, Cleveland Clinic27, Icahn School of Medicine at Mount Sinai28, University of Turin29, Université libre de Bruxelles30, Juntendo University31, National Cancer Research Institute32, Mayo Clinic33, University of Toronto34, Sinai Grace Hospital35, Netherlands Cancer Institute36, Hiroshima University37, City of Hope National Medical Center38, University of Chicago39, New York University40, Georgetown University41, University of Tokushima42, University of Pisa43, Osaka University44, University of Valencia45, Good Samaritan Hospital46, Military Medical Academy47, Fundación Favaloro48, Autonomous University of Barcelona49, Complutense University of Madrid50, University of Oviedo51, National and Kapodistrian University of Athens52, Rovira i Virgili University53, Autonomous University of Madrid54, Ghent University55
TL;DR: The methods used to evaluate the resultant Stage groupings and the proposals put forward for the 8th edition of the TNM Classification for lung cancer due to be published late 2016 are described.
2,826 citations
Constantine A. Gatsonis1, Denise R. Aberle2, Christine D. Berg, William C. Black3 +1333 more•Institutions (31)
TL;DR: The National Lung Screening Trial (NLST) is a randomized multicenter study comparing low-dose helical computed tomography with chest radiography in the screening of older current and former heavy smokers for early detection of lung cancer.
Abstract: The National Lung Screening Trial (NLST) is a randomized multicenter study comparing low-dose helical computed tomography (CT) with chest radiography in the screening of older current and former heavy smokers for early detection of lung cancer, which is the leading cause of cancer-related death in the United States Five-year survival rates approach 70% with surgical resection of stage IA disease; however, more than 75% of individuals have incurable locally advanced or metastatic disease, the latter having a 5-year survival of less than 5% It is plausible that treatment should be more effective and the likelihood of death decreased if asymptomatic lung cancer is detected through screening early enough in its preclinical phase For these reasons, there is intense interest and intuitive appeal in lung cancer screening with low-dose CT The use of survival as the determinant of screening effectiveness is, however, confounded by the well-described biases of lead time, length, and overdiagnosis Despite previous attempts, no test has been shown to reduce lung cancer mortality, an endpoint that circumvents screening biases and provides a definitive measure of benefit when assessed in a randomized controlled trial that enables comparison of mortality rates between screened individuals and a control group that does not undergo the screening intervention of interest The NLST is such a trial The rationale for and design of the NLST are presented
1,036 citations
University of Texas MD Anderson Cancer Center1, Foundation Medicine2, Bristol-Myers Squibb3, Memorial Sloan Kettering Cancer Center4, Harvard University5, Novartis6, University of California, Irvine7, Rabin Medical Center8, Tel Aviv University9, Sarah Cannon Research Institute10, Brigham and Women's Hospital11, University of Hong Kong12, New York University13
TL;DR: Genomic profiling may enhance the predictive utility of PD-L1 expression and tumor mutation burden and facilitate establishment of personalized combination immunotherapy approaches for genomically defined LUAC subsets.
Abstract: KRAS is the most common oncogenic driver in lung adenocarcinoma (LUAC). We previously reported that STK11/LKB1 (KL) or TP53 (KP) comutations define distinct subgroups of KRAS-mutant LUAC. Here, we examine the efficacy of PD-1 inhibitors in these subgroups. Objective response rates to PD-1 blockade differed significantly among KL (7.4%), KP (35.7%), and K-only (28.6%) subgroups (P < 0.001) in the Stand Up To Cancer (SU2C) cohort (174 patients) with KRAS-mutant LUAC and in patients treated with nivolumab in the CheckMate-057 phase III trial (0% vs. 57.1% vs. 18.2%; P = 0.047). In the SU2C cohort, KL LUAC exhibited shorter progression-free (P < 0.001) and overall (P = 0.0015) survival compared with KRASMUT;STK11/LKB1WT LUAC. Among 924 LUACs, STK11/LKB1 alterations were the only marker significantly associated with PD-L1 negativity in TMBIntermediate/High LUAC. The impact of STK11/LKB1 alterations on clinical outcomes with PD-1/PD-L1 inhibitors extended to PD-L1-positive non-small cell lung cancer. In Kras-mutant murine LUAC models, Stk11/Lkb1 loss promoted PD-1/PD-L1 inhibitor resistance, suggesting a causal role. Our results identify STK11/LKB1 alterations as a major driver of primary resistance to PD-1 blockade in KRAS-mutant LUAC.Significance: This work identifies STK11/LKB1 alterations as the most prevalent genomic driver of primary resistance to PD-1 axis inhibitors in KRAS-mutant lung adenocarcinoma. Genomic profiling may enhance the predictive utility of PD-L1 expression and tumor mutation burden and facilitate establishment of personalized combination immunotherapy approaches for genomically defined LUAC subsets. Cancer Discov; 8(7); 822-35. ©2018 AACR.See related commentary by Etxeberria et al., p. 794This article is highlighted in the In This Issue feature, p. 781.
978 citations
TL;DR: Measurements of lung tumor size on CT scans are often inconsistent and can lead to an incorrect interpretation of tumor response, but can be improved if the same reader performs serial measurements for any one patient.
Abstract: Purpose: Response of solid malignancies to therapy is usually determined by serial measurements of tumor size. The purpose of our study was to assess the consistency of measurements performed by readers evaluating lung tumors. Materials and Methods: The study group was composed of 33 patients with lung tumors more than 1.5 cm. Bidimensional (BD) and unidimensional (UD) measurements were performed on computed tomography (CT) scans according to the World Health Organization (WHO) criteria and the Response Evaluation Criteria in Solid Tumors (RECIST), respectively. Measurements were performed independently by five thoracic radiologists using printed film and were repeated after 5 to 7 days. Inter- and intraobserver measurement variations were estimated through statistical modeling. Results: There were 40 tumors with an average size of 1.8 to 8.0 cm (mean, 4.1 cm). Analysis of variance showed a significant difference (P < .05) among readers and among the measured nodules for UD and BD measurements. Interobser...
453 citations
Memorial Sloan Kettering Cancer Center1, Keio University2, Beth Israel Deaconess Medical Center3, Mount Sinai Hospital4, Yale University5, Fox Chase Cancer Center6, New Generation University College7, University of Chicago8, New York University9, Imperial College London10, Radboud University Nijmegen11, University of Barcelona12, Peter MacCallum Cancer Centre13, University of Michigan14, University of São Paulo15, Fred Hutchinson Cancer Research Center16, University of Duisburg-Essen17, Northern General Hospital18, University of Caen Lower Normandy19, Churchill Hospital20, Queen's University21, University of Sydney22, Sungkyunkwan University23, Seoul National University24, Kyorin University25, University of Copenhagen26, Nippon Medical School27, Katholieke Universiteit Leuven28, British Hospital29, University of Texas MD Anderson Cancer Center30, University of Antwerp31, Hyogo College of Medicine32, University of Western Australia33, Glenfield Hospital34, Cleveland Clinic35, Icahn School of Medicine at Mount Sinai36, University of Turin37, Université libre de Bruxelles38, Juntendo University39, National Cancer Research Institute40, Mayo Clinic41, Princess Margaret Cancer Centre42, Sinai Grace Hospital43, Netherlands Cancer Institute44, Hiroshima University45, City of Hope National Medical Center46, Georgetown University47, University of Tokushima48, University of Pisa49, Osaka University50
TL;DR: Codes for the primary tumor categories of AIS and minimally invasive adenocarcinoma (MIA) and a uniform way to measure tumor size in part‐solid tumors for the eighth edition of the tumor, node, and metastasis classification of lung cancer are proposed.
431 citations
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TL;DR: Screening with the use of low-dose CT reduces mortality from lung cancer, as compared with the radiography group, and the rate of death from any cause was reduced.
Abstract: Background The aggressive and heterogeneous nature of lung cancer has thwarted efforts to reduce mortality from this cancer through the use of screening. The advent of low-dose helical computed tomography (CT) altered the landscape of lung-cancer screening, with studies indicating that low-dose CT detects many tumors at early stages. The National Lung Screening Trial (NLST) was conducted to determine whether screening with low-dose CT could reduce mortality from lung cancer. Methods From August 2002 through April 2004, we enrolled 53,454 persons at high risk for lung cancer at 33 U.S. medical centers. Participants were randomly assigned to undergo three annual screenings with either low-dose CT (26,722 participants) or single-view posteroanterior chest radiography (26,732). Data were collected on cases of lung cancer and deaths from lung cancer that occurred through December 31, 2009. Results The rate of adherence to screening was more than 90%. The rate of positive screening tests was 24.2% with low-dose CT and 6.9% with radiography over all three rounds. A total of 96.4% of the positive screening results in the low-dose CT group and 94.5% in the radiography group were false positive results. The incidence of lung cancer was 645 cases per 100,000 person-years (1060 cancers) in the low-dose CT group, as compared with 572 cases per 100,000 person-years (941 cancers) in the radiography group (rate ratio, 1.13; 95% confidence interval [CI], 1.03 to 1.23). There were 247 deaths from lung cancer per 100,000 person-years in the low-dose CT group and 309 deaths per 100,000 person-years in the radiography group, representing a relative reduction in mortality from lung cancer with low-dose CT screening of 20.0% (95% CI, 6.8 to 26.7; P=0.004). The rate of death from any cause was reduced in the low-dose CT group, as compared with the radiography group, by 6.7% (95% CI, 1.2 to 13.6; P=0.02). Conclusions Screening with the use of low-dose CT reduces mortality from lung cancer. (Funded by the National Cancer Institute; National Lung Screening Trial ClinicalTrials.gov number, NCT00047385.).
7,710 citations
TL;DR: This new adenocarcinoma classification is needed to provide uniform terminology and diagnostic criteria, especially for bronchioloalveolar carcinoma (BAC), the overall approach to small nonresection cancer specimens, and for multidisciplinary strategic management of tissue for molecular and immunohistochemical studies.
3,850 citations
TL;DR: Defined regions of functionally active brown adipose tissue are present in adult humans, are more frequent in women than in men, and may be quantified noninvasively with the use of (18)F-FDG PET-CT.
Abstract: Background Obesity results from an imbalance between energy intake and expenditure. In rodents and newborn humans, brown adipose tissue helps regulate energy expenditure by thermogenesis mediated by the expression of uncoupling protein 1 (UCP1), but brown adipose tissue has been considered to have no physiologic relevance in adult humans. Methods We analyzed 3640 consecutive 18F-fluorodeoxyglucose (18F-FDG) positron-emission tomographic and computed tomographic (PET–CT) scans performed for various diagnostic reasons in 1972 patients for the presence of substantial depots of putative brown adipose tissue. Such depots were defined as collections of tissue that were more than 4 mm in diameter, had the density of adipose tissue according to CT, and had maximal standardized uptake values of 18F-FDG of at least 2.0 g per milliliter, indicating high metabolic activity. Clinical indexes were recorded and compared with those of date-matched controls. Immunostaining for UCP1 was performed on biopsy specimens from t...
3,805 citations
TL;DR: Qualitative and quantitative approaches to 18F-FDG PET response assessment have been applied and require a consistent PET methodology to allow quantitative assessments and the proposed PERCIST 1.0 criteria should serve as a starting point for use in clinical trials and in structured quantitative clinical reporting.
Abstract: The purpose of this article is to review the status and limitations of anatomic tumor response metrics including the World Health Organization (WHO) criteria, the Response Evaluation Criteria in Solid Tumors (RECIST), and RECIST 1.1. This article also reviews qualitative and quantitative approaches to metabolic tumor response assessment with 18 F-FDG PET and proposes a draft framework for PET Response Criteria in Solid Tumors (PERCIST), version 1.0. Methods: PubMed searches, including searches for the terms RECIST, positron, WHO, FDG, cancer (including specific types), treatment response, region of interest, and derivative references, were performed. Abstracts and articles judged most relevant to the goals of this report were reviewed with emphasis on limitations and strengths of the anatomic and PET approaches to treatment response assessment. On the basis of these data and the authors’ experience, draft criteria were formulated for PET tumor response to treatment. Results: Approximately 3,000 potentially relevant references were screened. Anatomic imaging alone using standard WHO, RECIST, and RECIST 1.1 criteria is widely applied but still has
3,094 citations
Imperial College London1, University of Barcelona2, Keio University3, University of Duisburg-Essen4, Queen's University5, Peter MacCallum Cancer Centre6, University of Michigan7, University of São Paulo8, Yale University9, Northern General Hospital10, University of Caen Lower Normandy11, Fred Hutchinson Cancer Research Center12, University of Oxford13, Memorial Sloan Kettering Cancer Center14, University of Sydney15, Sungkyunkwan University16, Seoul National University17, Kyorin University18, University of Copenhagen19, Nippon Medical School20, Katholieke Universiteit Leuven21, University of Texas MD Anderson Cancer Center22, University of Antwerp23, Hyogo College of Medicine24, University of Western Australia25, Glenfield Hospital26, Cleveland Clinic27, Icahn School of Medicine at Mount Sinai28, University of Turin29, Université libre de Bruxelles30, Juntendo University31, National Cancer Research Institute32, Mayo Clinic33, University of Toronto34, Sinai Grace Hospital35, Netherlands Cancer Institute36, Hiroshima University37, City of Hope National Medical Center38, University of Chicago39, New York University40, Georgetown University41, University of Tokushima42, University of Pisa43, Osaka University44, University of Valencia45, Good Samaritan Hospital46, Military Medical Academy47, Fundación Favaloro48, Autonomous University of Barcelona49, Complutense University of Madrid50, University of Oviedo51, National and Kapodistrian University of Athens52, Rovira i Virgili University53, Autonomous University of Madrid54, Ghent University55
TL;DR: The methods used to evaluate the resultant Stage groupings and the proposals put forward for the 8th edition of the TNM Classification for lung cancer due to be published late 2016 are described.
2,826 citations