The DOI matches its Crossref record; 71 of the 71 references it cites were found in a registry or an index; none of the 15 sources its claims cite is checked for support yet.
Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs
Open accessAbstract
IMPORTANCE: Targeting oncogenic drivers (genomic alterations critical to cancer development and maintenance) has transformed the care of patients with lung adenocarcinomas. The Lung Cancer Mutation Consortium was formed to perform multiplexed assays testing adenocarcinomas of the lung for drivers in 10 genes to enable clinicians to select targeted treatments and enroll patients into clinical trials. OBJECTIVES: To determine the frequency of oncogenic drivers in patients with lung adenocarcinomas and to use the data to select treatments targeting the identified driver(s) and measure survival. DESIGN, SETTING, AND PARTICIPANTS: From 2009 through 2012, 14 sites in the United States enrolled patients with metastatic lung adenocarcinomas and a performance status of 0 through 2 and tested their tumors for 10 drivers. Information was collected on patients, therapies, and survival. INTERVENTIONS: Tumors were tested for 10 oncogenic drivers, and results were used to select matched targeted therapies. MAIN OUTCOMES AND MEASURES: Determination of the frequency of oncogenic drivers, the proportion of patients treated with genotype-directed therapy, and survival. RESULTS: From 2009 through 2012, tumors from 1007 patients were tested for at least 1 gene and 733 for 10 genes (patients with full genotyping). An oncogenic driver was found in 466 of 733 patients (64%). Among these 733 tumors, 182 tumors (25%) had the KRAS driver; sensitizing EGFR, 122 (17%); ALK rearrangements, 57 (8%); other EGFR, 29 (4%); 2 or more genes, 24 (3%); ERBB2 (formerly HER2), 19 (3%); BRAF, 16 (2%); PIK3CA, 6 (<1%); MET amplification, 5 (<1%); NRAS, 5 (<1%); MEK1, 1 (<1%); AKT1, 0. Results were used to select a targeted therapy or trial in 275 of 1007 patients (28%). The median survival was 3.5 years (interquartile range [IQR], 1.96-7.70) for the 260 patients with an oncogenic driver and genotype-directed therapy compared with 2.4 years (IQR, 0.88-6.20) for the 318 patients with any oncogenic driver(s) who did not receive genotype-directed therapy (propensity score-adjusted hazard ratio, 0.69 [95% CI, 0.53-0.9], P = .006). CONCLUSIONS AND RELEVANCE: Actionable drivers were detected in 64% of lung adenocarcinomas. Multiplexed testing aided physicians in selecting therapies. Although individuals with drivers receiving a matched targeted agent lived longer, randomized trials are required to determine if targeting therapy based on oncogenic drivers improves survival. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT01014286.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
22 Own result · 11 Own method · 5 Not checked yet · 5 Own interpretation · 1 No basis given
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“2 or more genes, 24 (3%)”
- Also stated in: § Results · plain
“we found drivers in 2 genes in 24 tumors (3%).”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Abstract > RESULTS
plainn = 24- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Results · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The 190 patients with an oncogenic driver and treatment with a targeted agent had a median survival of 3.5 years (IQR, 1.96-7.70); the 248 with a driver and no targeted therapy, 2.5 years (P < .001”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Results
plaincorrelationaln = 190 ·- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“ERBB2 (formerly HER2), 19 (3%)”
- Also stated in: § Results · plain
“The frequencies of ERBB2 (all exon 20 insertions) were 3% (19 of 733 specimens)”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Abstract > RESULTS
plainn = 733- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Results · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The median survival was 3.5 years (interquartile range [IQR], 1.96-7.70) for the 260 patients with an oncogenic driver and genotype-directed therapy compared with 2.4 years (IQR, 0.88-6.20) for the 318 patients with any oncogenic driver(s) who did not receive genotype-directed therapy”
- Also stated in: § Results · plain
“The 260 patients with an oncogenic driver and treatment with a targeted agent had a median survival of 3.5 years; the 318 patients with a driver and no targeted therapy, 2.4 years”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Abstract > RESULTS
plaincorrelationaln = 260 ·- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Results · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“ALK rearrangements, 57 (8%)”
- Also stated in: § Results · plain
“ALK rearrangements occurred in 57 of 733 specimens (8%).”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Abstract > RESULTS
plainn = 733- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Results · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“An oncogenic driver was found in 466 of 733 patients (64%).”
- Also stated in: § Results · plain
“Among the 733 specimens tested for all 10 genes, 466 (64% [95% CI, 60%-67%) had an oncogenic driver”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Abstract > RESULTS
plainn = 733- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Results · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Among these 733 tumors, 182 tumors (25%) had the KRAS driver”
- Also stated in: § Results · plain
“KRAS mutations were the most frequent, found in 182 of 733 specimens (25%)”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Abstract > RESULTS
plainn = 733- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Results · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Overall, 28% (95% CI, 24%-30%) of eligible patients and 44% of individuals with drivers detected received a targeted therapy.”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Results
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The frequencies of drivers in the 1007 specimens in which at least 1 gene was assessed are presented in Table 2 and mirror the results with the patients’ tumors with full genotyping.”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Results
plainn = 1,007- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“BRAF, 16 (2%)”
- Also stated in: § Results · plain
“BRAF mutations were 2% (16 of 733 specimens)”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Abstract > RESULTS
plainn = 733- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Results · plain
- The quote only partly states this claim. 1
- It may state two separate claims as one. 8
- Probably not a substantial claim. 9
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“other EGFR, 29 (4%)”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Abstract > RESULTS
plaincorrelationaln = 733- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The quote only partly states this claim.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The LCMC characterized at least 1 gene for 91% (1007 of 1102 patients) of eligible patients with genotyping of all 10 genes in 66% (733 of 1102 patients).”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Discussion
plainn = 1,102- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The median potential follow-up was 2.0 years.”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Results
plainn = 938- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The 49 patients with oncogenic drivers other than EGFR or ALK who received a targeted therapy had a median survival of 4.9 years compared with the 678 with (318 patients) or without (360 patients) a driver identified, but not receiving a targeted agent, whose median survivals were 2.4 years with a driver (IQR, 0.88-6.20) and 2.1 years without (P = .14”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Results
plainn = 49- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Of the 175 patients (83%) with EGFR(s) mutations, 146 were treated with targeted therapy: 130 with erlotinib alone, and 16 with another EGFR inhibitor alone or in combination.”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Results
plainn = 175- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Patients in the driver + treatment group had a 5% better performance status, a 3-year lower median age, and were more likely to be never smokers (Table 1); factors that could lead to an improved prognosis.”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Discussion
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Multiplexed testing aided physicians in selecting therapies.”
- Also stated in: § Conclusions · plain
“Multiplexed testing aided physicians in selecting therapies and patients for targeted trials.”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Abstract > CONCLUSIONS AND RELEVANCE
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Also stated in: § Conclusions · plain
None of the sources cited for this claim have been checked yet.
In the paper
“Testing for somatic mutations in the epidermal growth factor receptor (EGFR) gene4-6 and rearrangements of the anaplastic lymphoma kinase (ALK) gene7 is now routine.8”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Abstract > CONCLUSIONS AND RELEVANCE
What the sources say
- Not checked yetcites [4] Lynch TJ Bell DW Sordella R Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small cell lung cancer to gefitinib N Engl J Med 2004 350 21 2129 2139 15118073
- Not checked yetcites [5] Paez JG Jänne PA Lee JC EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy Science 2004 304 5676 1497 1500 15118125
- Not checked yetcites [6] Pao W Miller V Zakowski M EGF receptor gene mutations are common in lung cancers from “never smokers” and are associated with sensitivity of tumors to gefitinib and erlotinib Proc Natl Acad SciUS A 2004 101 36 13306 13311 PMC516528 15329413
- Not checked yetcites [7] Kwak EL Bang YJ Camidge DR Anaplastic lymphoma kinase inhibition in non-small cell lung cancer N Engl J Med 2010 363 18 1693 1703 20979469 PMC3014291
- Not checked yetcites [8] National Comprehensive Cancer Network NCCN clinical practice guidelines in oncology 2014 http://www.nccn.org/professionals/physician_gls/f_guidelines.asp. Accessed April 21
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Adenocarcinoma was centrally confirmed.”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Methods > Patients
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The LCMC clinical committee chairs reviewed the records of each patient with an oncogenic driver and the targeted agent administered to verify that the treatment was directed against that driver(s) detected in the patient’s tumor.”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Methods > Interventions
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“With the proposed sample size of 1000, the half-width of the 95% CI is less than 5% if the oncogenic driver rate is less than 40%.”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Methods > Statistical Methods
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The decision to recommend a targeted therapy to a patient with a tumor harboring an oncogenic driver was left to the treating physician.”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Methods > Interventions
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The knowledge-based confounding variables adjusted in the propensity model were sex, age at enrollment, performance status, smoking history, stage at diagnosis, prior therapy (surgery, chest radiotherapy, or chemotherapy), and elapsed time from metastatic disease diagnosis to study enrollment (years).”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Methods > Statistical Methods
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Criteria for specimen adequacy were not prespecified.”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Methods > Interventions
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“The LCMC effort differs from other genomic characterization efforts, like the Cancer Genome Atlas that studied patients with localized disease and obtained tissues exclusively from resection specimens.35-40”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Discussion
What the sources say
- Not checked yetcites [35] Weir BA Woo MS Getz G Characterizing the cancer genome in lung adenocarcinoma Nature 2007 450 7171 893 898 17982442 PMC2538683
- Not checked yetcites [36] Barletta JA Perner S Iafrate AJ Clinical significance of TTF-1 protein expression and TTF-1 gene amplification in lung adenocarcinoma J Cell Mol Med 2009 13 8B 1977 1986 19040416 PMC2830395
- Not checked yetcites [37] Hammerman PS Sos ML Ramos AH Mutations in the DDR2 kinase gene identify a novel therapeutic target in squamous cell lung cancer Cancer Discov 2011 1 1 78 89 22328973 PMC3274752
- Not checked yetcites [38] Cancer Genome Atlas Research Network Comprehensive genomic characterization of squamous cell lung cancers Nature 2012 489 7417 519 525 [published online September 27, 2012] 22960745 PMC3466113
- Not checked yetcites [39] D’Angelo SP Janjigian YY Ahye N Distinct clinical course of EGFR-mutant resected lung cancers: results of testing of 1118 surgical specimens and effects of adjuvant gefitinib and erlotinib J Thorac Oncol 2012 7 12 1815 1822 23154553
- Not checked yetcites [40] Peifer M Fernández-Cuesta L Sos ML Integrative genome analyses identify key somatic driver mutations of small cell lung cancer Nat Genet 2012 44 10 1104 1110 22941188 PMC4915822
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The LCMC pathologists shared blinded samples, with a positive sample included for all 10 drivers.”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Methods > Interventions
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The multiplexed genotyping platforms made effective use of patient tissue and identified actionable drivers sooner, giving patient’s earlier access to therapies or trials.”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Discussion
plaindirectn = 18- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“The presence of EGFR mutations defines a specific molecular subgroup of NSCLC (~15% of Caucasian patients with adenocarcinomas) [37, 38] that respond to an EGFR TKI in over 60% of patients (Table 1).”
From A decade of EGFR inhibition in EGFR-mutated non small cell lung cancer (NSCLC): Old successes and future perspectives (2015) · cites this paper as [38]
In the citing paper
“Somatic mutations in the kinase domain of the epidermal growth factor receptor (EGFR) gene are detected in approximately 40% and 17% of lung adenocarcinoma in Asians1 and in Caucasians,2 respectively.”
From Not all epidermal growth factor receptor mutations in lung cancer are created equal: Perspectives for individualized treatment strategy (2016) · cites this paper as [2]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated major: it would touch a result — a value a result rests on, reported and recomputed p-values on opposite sides of the significance level, two passages that conflict with no sign which is right, or a cited work retracted before this paper was published.
In the paper
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Results
“Amplification of MET (MET/ CEP7 >2.2) was found in 5 of 733 patients’ tumors (<1%).”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Results
“In the full genotyping group, we found drivers in 2 genes in 24 tumors (3%). Of these 24 specimens, 20 (83%) included either a mutation in PIK3CA (n = 12) or MET amplification (n = 8).”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
“Results were used to select a targeted therapy or trial in 275 of 1007 patients (28%).”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Abstract > RESULTS
Reported 28 · recomputed 27.308838
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Results
“We also recomputed the survival data excluding individuals with EGFR- and ALK-positive cancers. The 49 patients with oncogenic drivers other than EGFR or ALK who received a targeted therapy had a median survival of 4.9 years compared with the 678 with (318 patients) or without (360 patients) a driver identified, but not receiving a targeted agent, whose median survivals were 2.4 years with a driver (IQR, 0.88-6.20) and 2.1 years without (P = .14; eFigure 6 in the Supplement).”
§ Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs > Discussion
“survival analyses excluding these patients revealed that individuals with other drivers treated with targeted therapies still had an observed 2.5-year improvement in median survival over those who did not receive targeted therapy (eFigure 4 in the Supplement).”
Citations
Cites
Siegel, R., Ma, J., Zou, Z., & Jemal, A. (2014) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21208 · Cited by 11,499
Lynch, T. J., Bell, D. W., Sordella, R., Gurubhagavatula, S., Okimoto, R. A., Brannigan, B. W., Harris, P. L., Haserlat, S. M., Supko, J. G., Haluska, F. G., et al. (2004) · New England Journal of Medicine · doi:10.1056/nejmoa040938 · Cited by 11,486
EGFR Mutations in Lung Cancer: Correlation with Clinical Response to Gefitinib Therapy
Paez, J. G., Jänne, P. A., Lee, J. C., Tracy, S., Greulich, H., Gabriel, S., Herman, P., Kaye, F. J., Lindeman, N., Boggon, T. J., et al. (2004) · Science · doi:10.1126/science.1099314 · Cited by 9,368
Self-citationGefitinib or Carboplatin–Paclitaxel in Pulmonary Adenocarcinoma
Mok, T. S., Wu, Y.-L., Thongprasert, S., Yang, C.-H., Chu, D.-T., Saijo, N., Sunpaweravong, P., Han, B., Margono, B., Ichinose, Y., et al. (2009) · New England Journal of Medicine · doi:10.1056/nejmoa0810699 · Cited by 8,261
Identification of the transforming EML4–ALK fusion gene in non-small-cell lung cancer
Soda, M., Choi, Y. L., Enomoto, M., Takada, S., Yamashita, Y., Ishikawa, S., Fujiwara, S.-I., Watanabe, H., Kurashina, K., Hatanaka, H., et al. (2007) · Nature · doi:10.1038/nature05945 · Cited by 5,439
Anaplastic Lymphoma Kinase Inhibition in Non–Small-Cell Lung Cancer
Kwak, E. L., Bang, Y., Camidge, D. R., Shaw, A. T., Solomon, B., Maki, R. G., Ou, S. I., Dezube, B. J., Janne, P. A., Costa, D. B., et al. (2010) · New England Journal of Medicine · doi:10.1056/nejmoa1006448 · Cited by 4,477
Self-citationPao, W., Miller, V., Zakowski, M., Doherty, J., Politi, K., Sarkaria, I., Singh, B., Heelan, R., Rusch, V., Fulton, L., et al. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0405220101 · Cited by 4,338
Self-citationComprehensive genomic characterization of squamous cell lung cancers
The Cancer Genome Atlas Research Network (2012) · Nature · doi:10.1038/nature11404 · Cited by 3,994
Self-citationSequist, L. V., Yang, J. C.-H., Yamamoto, N., O'Byrne, K., Hirsh, V., Mok, T., Geater, S. L., Orlov, S., Tsai, C.-M., Boyer, M., et al. (2013) · Journal of Clinical Oncology · doi:10.1200/jco.2012.44.2806 · Cited by 3,228
Self-citationFirst-Line Crizotinib versus Chemotherapy in ALK -Positive Lung Cancer
Solomon, B. J., Mok, T., Kim, D.-W., Wu, Y.-L., Nakagawa, K., Mekhail, T., Felip, E., Cappuzzo, F., Paolini, J., Usari, T., et al. (2014) · New England Journal of Medicine · doi:10.1056/nejmoa1408440 · Cited by 3,190
Cited by
Sorted by citations
Items 201–300 of 1,000
Shen, Y.-C., Tseng, G.-C., Tu, C.-Y., Chen, W.-C., Liao, W.-C., Chen, W.-C., Li, C.-H., Chen, H.-J., & Hsia, T.-C. (2017) · Lung Cancer · doi:10.1016/j.lungcan.2017.06.007 · Cited by 99
Self-citationProspective Clinical Study of Precision Oncology in Solid Tumors
Sohal, D. P. S., Rini, B. I., Khorana, A. A., Dreicer, R., Abraham, J., Procop, G. W., Saunthararajah, Y., Pennell, N. A., Stevenson, J. P., Pelley, R. J., et al. (2015) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djv332 · Cited by 97
Precision medicine needs randomized clinical trials
Saad, E. D., Paolettí, X., Burzykowski, T., & Buyse, M. E. (2017) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2017.8 · Cited by 98
Zhai, X., Zhang, J., Tian, Y., Li, J., Wang, J., Guo, H., & Zhu, H. (2020) · Cancer Biology and Medicine · doi:10.20892/j.issn.2095-3941.2020.0102 · Cited by 99
Breakthrough in targeted therapy for non-small cell lung cancer
Zhencong, Y., Huang, Y., Ke, J., Zhu, X. M., Leng, S., & Luo, H. (2020) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2020.111079 · Cited by 100
Patient-Centered Palliative Care for Patients With Advanced Lung Cancer
Temel, J. S., Petrillo, L. A., & Greer, J. A. (2022) · Journal of Clinical Oncology · doi:10.1200/jco.21.01710 · Cited by 102
Osimertinib in the treatment of non-small-cell lung cancer: design, development and place in therapy
Santarpía, M., Liguori, A., Karachaliou, N., González‐Cao, M., Daffinà, M. G., D’Aveni, A., Marabello, G., Altavilla, G., & Rosell, R. (2017) · Lung Cancer Targets and Therapy · doi:10.2147/lctt.s119644 · Cited by 104
Domagala-Kulawik, J. J. (2015) · PubMed Central · doi:10.3978/j.issn.2218-6751.2015.01.11 · Cited by 94
Mino-Kenudson, M. A., & Mino-Kenudson, M. A. (2016) · Cancer Biology and Medicine · doi:10.20892/j.issn.2095-3941.2016.0009 · Cited by 93
Griesinger, F., Eberhardt, W., Nusch, A., Reiser, M., Zahn, M., Maintz, C., Bernhardt, C., Losem, C. J., Stenzinger, A., Heukamp, L. C., et al. (2020) · Lung Cancer · doi:10.1016/j.lungcan.2020.10.012 · Cited by 93
Xu, J., Jin, B., Chu, T., Dong, X., Yang, H., Zhang, Y., Wu, D., Lou, Y., Zhang, X., Wang, H., et al. (2016) · Lung Cancer · doi:10.1016/j.lungcan.2016.01.018 · Cited by 92
Non–Small Cell Lung Cancer, PD-L1, and the Pathologist
Kerr, K. M., & Nicolson, M. C. (2016) · Archives of Pathology & Laboratory Medicine · doi:10.5858/arpa.2015-0303-sa · Cited by 92
Nair, J. K. R., Saeed, U. A., McDougall, C. C., Sabri, A., Kovacina, B., Raidu, B. V. S., Khokhar, R. A., Probst, S., Hirsh, V., Chankowsky, J., et al. (2020) · Canadian Association of Radiologists Journal · doi:10.1177/0846537119899526 · Cited by 91
Can EGFR be a therapeutic target in breast cancer?
Li, X., Zhao, L., Chen, C., Nie, J., & Jiao, B. (2022) · Biochimica et Biophysica Acta (BBA) - Reviews on Cancer · doi:10.1016/j.bbcan.2022.188789 · Cited by 96
Reguart, N., & Remon, J. (2015) · Future Oncology · doi:10.2217/fon.15.15 · Cited by 91
EGFR mutation, smoking, and gender in advanced lung adenocarcinoma
Tseng, C., Chiang, C., Tseng, J., Yang, T., Hsu, K.-H., Chen, K., Wang, C.-L., Chen, C., Yen, S.-H., Tsai, C., et al. (2017) · Oncotarget · doi:10.18632/oncotarget.21842 · Cited by 90
Self-citationFrequency and outcomes of brain metastases in patients with HER2‐mutant lung cancers
Offin, M. D., Feldman, D., Ni, A., Myers, M. L., Lai, W. V., Pentsova, E. I., Boire, A. A., Daras, M., Jordan, E., Solit, D. B., et al. (2019) · Cancer · doi:10.1002/cncr.32461 · Cited by 89
Self-citationTian, S. K., Killian, J. K., Rekhtman, N., Benayed, R., Middha, S., Ladanyi, M., Lin, O., & Arcila, M. E. (2016) · Archives of Pathology & Laboratory Medicine · doi:10.5858/arpa.2016-0108-ra · Cited by 88
Self-citationHuynh, T. G., Morales‐Oyarvide, V., Campo, M. J., Gainor, J. F., Bozkurtlar, E. B., Uruga, H., Zhao, L. P., Gomez‐Caraballo, M., Hata, A. N., Mark, E. J., et al. (2016) · Journal of Thoracic Oncology · doi:10.1016/j.jtho.2016.08.134 · Cited by 88
Hayashi, H., Kohno, T., Ueno, H., Hiraoka, N., Kondo, S., Saito, M., Shimada, Y., Ichikawa, H., Kato, M., Shibata, T., et al. (2017) · Pancreas · doi:10.1097/mpa.0000000000000760 · Cited by 88
TAS6417, A Novel EGFR Inhibitor Targeting Exon 20 Insertion Mutations
Hasako, S., Terasaka, M., Abe, N., Uno, T., Ohsawa, H., Hashimoto, A., Fujita, R., Tanaka, K., Okayama, T., Wadhwa, R., et al. (2018) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.mct-17-1206 · Cited by 88
Precision medicine: lessons learned from the SHIVA trial
Tsimberidou, A. M., & Kurzrock, R. (2015) · The Lancet Oncology · doi:10.1016/s1470-2045(15)00397-6 · Cited by 88
Banno, E., Togashi, Y., Nakamura, Y., Chiba, M., Kobayashi, Y., Hayashi, H., Terashima, M., de Velasco, M. A., Sakai, K., Fujita, Y., et al. (2016) · Cancer Science · doi:10.1111/cas.12980 · Cited by 87
Chemotherapy for Lung Cancer in the Era of Personalized Medicine
Lee, S. H. (2018) · Tuberculosis & respiratory diseases · doi:10.4046/trd.2018.0068 · Cited by 91
Genomics and the History of Precision Oncology
Doroshow, D. B., & Doroshow, J. H. (2019) · Surgical Oncology Clinics of North America · doi:10.1016/j.soc.2019.08.003 · Cited by 93
Tumor Immunology and Immunotherapy of Non-Small-Cell Lung CancerPreprint
Cascone, T., Fradette, J. J., Pradhan, M., & Gibbons, D. L. (2021) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a037895 · Cited by 91
Liu, L., Liu, J., Шао, Д., Deng, Q., Tang, H., Zu, L., Chen, X., Guo, F., Lin, Y., Mao, M., et al. (2017) · Cancer Science · doi:10.1111/cas.13410 · Cited by 87
Peters, S., Fontecedro, A. C., Nechushtan, H., Shih, J., Liao, W., Gautschi, O. P., Spataro, V. J., Unk, M., Yang, J. C., Lorence, R. M., et al. (2018) · Journal of Thoracic Oncology · doi:10.1016/j.jtho.2018.07.093 · Cited by 85
Al‐Kateb, H., Nguyen, T. T., Steger-May, K., & Pfeifer, J. D. (2015) · Molecular Oncology · doi:10.1016/j.molonc.2015.05.004 · Cited by 84
Current challenges of metastatic breast cancer
Lim, B., & Hortobágyi, G. N. (2016) · Cancer and Metastasis Reviews · doi:10.1007/s10555-016-9636-y · Cited by 87
Masood, A., Kancha, R. K., & Subramanian, J. (2019) · Seminars in Oncology · doi:10.1053/j.seminoncol.2019.08.004 · Cited by 86
Matikas, A., Mistriotis, D., Georgoulias, V., & Kotsakis, A. P. (2016) · Critical Reviews in Oncology/Hematology · doi:10.1016/j.critrevonc.2016.12.005 · Cited by 82
Chong, C. R., Bahcall, M., Capelletti, M., Kosaka, T., Ercan, D., Sim, T., Sholl, L. M., Nishino, M., Johnson, B. E., Gray, N. S., et al. (2016) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-15-1601 · Cited by 81
Self-citationSalehi‐Rad, R., Li, R., Paul, M. K., Dubinett, S. M., & Liu, B. (2020) · Clinics in Chest Medicine · doi:10.1016/j.ccm.2019.10.003 · Cited by 85
Sebastian, M., Eberhardt, W., Hoffknecht, P., Metzenmacher, M., Wehler, T., Kokowski, K., Alt, J. A., Schütte, W., Büttner, R., Heukamp, L. C., et al. (2021) · Lung Cancer · doi:10.1016/j.lungcan.2021.02.005 · Cited by 83
Wang, R., Zhang, Y., Pan, Y., Li, Y., Hu, H., Cai, D., Li, H., Ye, T., Luo, X., Zhang, Y., et al. (2015) · Oncotarget · doi:10.18632/oncotarget.5549 · Cited by 82
Self-citationJorge, S. E., Schulman, S., Freed, J. A., VanderLaan, P. A., Rangachari, D., Kobayashi, S. S., Huberman, M. S., & Costa, D. B. (2015) · Lung Cancer · doi:10.1016/j.lungcan.2015.10.028 · Cited by 82
Takeda, M., Sakai, K., Terashima, M., Kaneda, H., Hayashi, H., Tanaka, K., Okamoto, K., Takahama, T., Yoshida, T., Iwasa, T., et al. (2015) · Annals of Oncology · doi:10.1093/annonc/mdv475 · Cited by 80
Kukita, Y., Matoba, R., Uchida, J., Hamakawa, T., Doki, Y., Imamura, F., & Kato, K. (2015) · DNA Research · doi:10.1093/dnares/dsv010 · Cited by 80
Rozenblum, A. B., Ilouze, M., Dudnik, E., Dvir, A., Soussan‐Gutman, L., Geva, S., & Peled, N. (2016) · Journal of Thoracic Oncology · doi:10.1016/j.jtho.2016.10.021 · Cited by 80
The Importance of Biopsy in the Era of Molecular Medicine
Ziv, E., Durack, J. C., & Solomon, S. B. (2016) · The Cancer Journal · doi:10.1097/ppo.0000000000000228 · Cited by 80
Brain Metastases in Oncogene-Addicted Non-Small Cell Lung Cancer Patients: Incidence and Treatment
Remón, J., & Besse, B. (2018) · Frontiers in Oncology · doi:10.3389/fonc.2018.00088 · Cited by 80
Yin, W., Yu, X., Kang, X., Zhao, Y., Zhao, P., Jin, H., Fu, X., Wan, Y., Peng, C., & Huang, Y. (2018) · Small · doi:10.1002/smll.201802372 · Cited by 80
Targeting Autophagy for Overcoming Resistance to Anti-EGFR Treatments
Kwon, Y., Kim, M.-S., Jung, H. S., Kim, Y., & Jeoung, D. (2019) · Cancers · doi:10.3390/cancers11091374 · Cited by 82
Basket Studies: Redefining Clinical Trials in the Era of Genome-Driven Oncology
Tao, J. J., Schram, A. M., & Hyman, D. M. (2017) · Annual Review of Medicine · doi:10.1146/annurev-med-062016-050343 · Cited by 84
Ebisudani, T., Hamamoto, J., Togasaki, K., Mitsuishi, A., Sugihara, K., Shinozaki, T., Fukushima, T., Kawasaki, K., Seino, T., Oda, M., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112212 · Cited by 81
Lai, W. V., Lebas, L., Barnes, T. A., Milia, J., Ni, A., Gautschi, O. P., Peters, S., Ferrara, R., Plodkowski, A. J., Kavanagh, J., et al. (2019) · European Journal of Cancer · doi:10.1016/j.ejca.2018.11.030 · Cited by 79
Self-citationSteuten, L., Goulart, B. H. L., Meropol, N. J., Pritchard, D. E., & Ramsey, S. D. (2019) · JCO Clinical Cancer Informatics · doi:10.1200/cci.19.00002 · Cited by 78
NSCLC and HER2: between lights and shadows
Ricciardi, G. R. R., Russo, A., Franchina, T., Ferraro, G., Zanghì, M., Picone, A., Scimone, A., & Adamo, V. (2014) · Journal of Thoracic Oncology · doi:10.1097/jto.0000000000000379 · Cited by 78
Targeted Therapy for Brain Metastases in EGFR-Mutated and ALK-Rearranged Non-Small-Cell Lung Cancer
Baik, C. S., Chamberlain, M. C., & Chow, L. Q. M. (2015) · Journal of Thoracic Oncology · doi:10.1097/jto.0000000000000615 · Cited by 77
Hirshfield, K. M., Tolkunov, D., Zhong, J., Ali, S. M., Stein, M. N., Murphy, S., Vig, H. S., Vázquez, A., Glod, J. W., Moss, R. A., et al. (2016) · The Oncologist · doi:10.1634/theoncologist.2016-0049 · Cited by 80
Jurišić, V., Vuković, V., Obradović, J., Gulyaeva, L. F., Кушлинский, Н. Е., & Djordjević, N. (2020) · Journal of Oncology · doi:10.1155/2020/1973241 · Cited by 80
Suzawa, K., Toyooka, S., Sakaguchi, M., Morita, M., Yamamoto, H., Tomida, S., Ohtsuka, T., Watanabe, M., Hashida, S., Maki, Y., et al. (2015) · Cancer Science · doi:10.1111/cas.12845 · Cited by 77
Biopsy-free circulating tumor DNA assay identifies actionable mutations in lung cancer
Villaflor, V., Won, B., Nagy, R., Banks, K., Lanman, R. B., Talasaz, A., & Salgia, R. (2016) · Oncotarget · doi:10.18632/oncotarget.11801 · Cited by 75
Shin, D. H., Lee, D., Hong, D. W., Hong, S. H., Hwang, J.-A., Lee, B. I., You, H. J., Lee, G. K., Kim, I.-H., Lee, Y.-S., et al. (2016) · Oncotarget · doi:10.18632/oncotarget.11913 · Cited by 78
Tsimberidou, A. M., Hong, D. S., Wheler, J. J., Falchook, G. S., Jankú, F., Naing, A., Fu, S., Piha-Paul, S. A., Cartwright, C., Broaddus, R. R., et al. (2019) · Journal of Hematology & Oncology · doi:10.1186/s13045-019-0835-1 · Cited by 76
Tan, D. S. W., Leighl, N. B., Riely, G. J., Yang, J. C., Sequist, L. V. D., Wolf, J., Seto, T., Felip, E., Ponce-Aix, S., Jonnaert, M., et al. (2020) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(19)30267-x · Cited by 75
Self-citationBRAF-Mutated Non-Small Cell Lung Cancer: Current Treatment Status and Future Perspective
Yan, N., Guo, S., Zhang, H., Zhang, Z., Shen, S., & Li, X. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.863043 · Cited by 80
The evolving role of liquid biopsy in lung cancer
Malapelle, U., Pisapia, P., Pepe, F., Russo, G., Buono, M., Russo, A., Gomez, J. E., Khorshid, O., Mack, P. C., Rolfo, C. D., et al. (2022) · Lung Cancer · doi:10.1016/j.lungcan.2022.08.004 · Cited by 77
Blood-based tumor biomarkers in lung cancer for detection and treatment
Mamdani, H. M., Ahmed, S. S., Armstrong, S. A., Mok, T. S. K., & Jalal, S. I. (2017) · Translational Lung Cancer Research · doi:10.21037/tlcr.2017.09.03 · Cited by 75
MEK inhibition in non-small cell lung cancer
Stinchcombe, T. E., & Johnson, G. L. (2014) · Lung Cancer · doi:10.1016/j.lungcan.2014.09.005 · Cited by 69
Meyer, N. J., & Calfee, C. S. (2017) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(17)30187-x · Cited by 74
Sugimoto, A. K., Matsumoto, S., Udagawa, H., Itotani, R., Usui, Y., Umemura, S., Nishino, K., Nakachi, I., Kuyama, S., Daga, H., et al. (2022) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-22-1749 · Cited by 73
Gibbs, S. N., Peneva, D., Carter, G. C., Palomares, M. R., Thakkar, S. G., Hall, D. W., Dalglish, H., Campos, C., & Yermilov, I. (2023) · JCO Precision Oncology · doi:10.1200/po.22.00715 · Cited by 72
Patient‐derived xenograft model in cancer: establishment and applications
Gu, A., Li, J., Li, M., & Liu, Y. (2025) · MedComm · doi:10.1002/mco2.70059 · Cited by 82
The Unique Characteristics of MET Exon 14 Mutation in Chinese Patients with NSCLC
Liu, S. M., Gou, L.-Y., Li, A., Lou, N.-N., Gao, H., Su, J., Yang, J., Zhang, X., Shao, Y. W., Dong, Z., et al. (2016) · Journal of Thoracic Oncology · doi:10.1016/j.jtho.2016.05.016 · Cited by 73
Frumovitz, M., Burzawa, J. K., Byers, L. A., Lyons, Y. A., Ramalingam, P., Coleman, R. L., & Brown, J. (2016) · Gynecologic Oncology · doi:10.1016/j.ygyno.2016.04.001 · Cited by 71
Current and Future Molecular Testing in NSCLC, What Can We Expect from New Sequencing Technologies?
Garinet, S., Laurent‐Puig, P., Blons, H., & Oudart, J. (2018) · Journal of Clinical Medicine · doi:10.3390/jcm7060144 · Cited by 71
Targeting HER2 expression in cancer: New drugs and new indications
Vranić, S., Bešlija, S., & Gatalica, Z. (2020) · Biomolecules and Biomedicine · doi:10.17305/bjbms.2020.4908 · Cited by 79
Koga, T., Kobayashi, Y., Tomizawa, K., Suda, K., Kosaka, T., Sesumi, Y., Fujino, T., Nishino, M., Ohara, S., Chiba, M., et al. (2018) · Lung Cancer · doi:10.1016/j.lungcan.2018.10.019 · Cited by 70
de la Rocha, A. A., Berlow, N., Fader, M. E., Coats, E. R., Saghira, C., Espinal, P. S., Galano, J., Khatib, Z. A., Abdella, H., Maher, O. M., et al. (2024) · Nature Medicine · doi:10.1038/s41591-024-02848-4 · Cited by 75
Tumor Heterogeneity and Therapeutic Resistance
Lovly, C. M., Salama, A. K. S., & Salgia, R. (2016) · American Society of Clinical Oncology Educational Book · doi:10.1200/edbk_158808 · Cited by 74
Wiesweg, M., Eberhardt, W., Reis, H., Ting, S. C., Savvidou, N., Skiba, C., Herold, T., Christoph, D. C., Meiler, J., Worm, K., et al. (2016) · Journal of Thoracic Oncology · doi:10.1016/j.jtho.2016.08.137 · Cited by 69
Raez, L. E., Cardona, A. F., Santos, E. S., Catoe, H. W., Rolfo, C. D., Lopes, G. D. L., Jr., Barrios, C. H., Mas, L. A., Vallejos, C. S., Zatarain-Barrón, Z. L., et al. (2018) · Lung Cancer · doi:10.1016/j.lungcan.2018.02.014 · Cited by 70
Chen, L.-Y., Molina-Vila, M. A., Ruan, S.-Y., Su, K.-Y., Liao, W.-Y., Yu, K.-L., Ho, C.-C., Shih, J.-Y., Yu, C.-J., Yang, J. C.-H., et al. (2016) · Lung Cancer · doi:10.1016/j.lungcan.2016.01.019 · Cited by 67
Reguart, N., Teixidó, C., Giménez-Capitán, A. A., Paré, L., Galván, P., Viteri, S., Rodríguez, S., Peg, V., Aldeguer, E., Viñolas, N., et al. (2017) · Clinical Chemistry · doi:10.1373/clinchem.2016.265314 · Cited by 68
Overcoming drug resistance to receptor tyrosine kinase inhibitors: Learning from lung cancer
Kuwano, M., Sonoda, K., Murakami, Y., Watari, K., & Ono, M. (2016) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2016.03.002 · Cited by 66
Lin, Q. D., Zhang, H., Ding, H., Qian, J., Lizaso, A., Lin, J., Han‐Zhang, H., Xiang, J., Li, Y., & Zhu, H. (2019) · Journal of Translational Medicine · doi:10.1186/s12967-019-2036-7 · Cited by 67
Zwierenga, F., van Veggel, B. A. M. H., Hendriks, L. E. L., Hiltermann, T. J. N., Hiddinga, B. I., Hijmering-Kappelle, L. B. M., ter Elst, A., Hashemi, S. M. S., Dingemans, A. C., van der Leest, C., et al. (2022) · Lung Cancer · doi:10.1016/j.lungcan.2022.06.012 · Cited by 70
Muto, S., Enta, A., Maruya, Y., Inomata, S., Yamaguchi, H., Mine, H., Takagi, H., Ozaki, Y., Watanabe, M., Inoue, T., et al. (2023) · Biomedicines · doi:10.3390/biomedicines11010190 · Cited by 68
Zhao, Y. S., Xiong, S., Ren, Q., Wang, J., Li, M., Yang, L., Wu, D., Tang, K., Pan, X., Chen, F., et al. (2024) · The Lancet Oncology · doi:10.1016/s1470-2045(24)00599-0 · Cited by 70
Sullivan, I., & Planchard, D. (2016) · Therapeutic Advances in Respiratory Disease · doi:10.1177/1753465816670498 · Cited by 65
Guibert, N. M., Barlési, F., Descourt, R., Léna, H., Besse, B., Beau‐Faller, M., Mosser, J., Pichon, É., Merlio, J., Ouafik, L., et al. (2017) · Journal of Thoracic Oncology · doi:10.1016/j.jtho.2017.02.001 · Cited by 65
Yoda, S., Dagogo‐Jack, I., & Hata, A. N. (2018) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2018.08.007 · Cited by 68
NTRK Fusion-positive Non–small-cell Lung Cancer: The Diagnosis and Targeted Therapy
Haratake, N., & Seto, T. (2020) · Clinical Lung Cancer · doi:10.1016/j.cllc.2020.10.013 · Cited by 65
Current Status of CTCs as Liquid Biopsy in Lung Cancer and Future Directions
Zhang, Z., Ramnath, N., & Nagrath, S. (2015) · Frontiers in Oncology · doi:10.3389/fonc.2015.00209 · Cited by 64
Langer, C. J., Obasaju, C. K., Bunn, P. A., Bonomi, P., Gandara, D. R., Hirsch, F. R., Kim, E. S., Natale, R. B., Novello, S., Paz-Ares, L. G., et al. (2016) · Journal of Thoracic Oncology · doi:10.1016/j.jtho.2016.08.138 · Cited by 62
Self-citationHung, J., Yen, M., Jian, S., Wu, C., Chang, W., Liu, K., Hsu, Y., Chong, I., & Kuo, P. (2017) · Oncotarget · doi:10.18632/oncotarget.19475 · Cited by 64
Precision Oncology Decision Support: Current Approaches and Strategies for the Future
Kurnit, K. C., Dumbrava, E. E. I., Litzenburger, B. C., Khotskaya, Y. B., Johnson, A. M., Yap, T. A., Rodon, J. A., Zeng, J., Shufean, M. A., Bailey, A. M., et al. (2018) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-17-2494 · Cited by 64
Kim, E. K., Kim, K., Lee, C. Y., Kim, S., Chang, S. H., Cho, B. C., & Shim, H. S. (2018) · Clinical Lung Cancer · doi:10.1016/j.cllc.2018.10.004 · Cited by 63
Precision medicine in NSCLC and pathology: how does ALK fit in the pathway?
Kerr, K. M., & López‐Ríos, F. (2016) · Annals of Oncology · doi:10.1093/annonc/mdw302 · Cited by 63
Tomasello, C., Baldessari, C., Napolitano, M., Orsi, G., Grizzi, G., Bertolini, F., Barbieri, F., & Cascinu, S. (2018) · Critical Reviews in Oncology/Hematology · doi:10.1016/j.critrevonc.2018.01.013 · Cited by 65
Mechanisms of primary resistance to EGFR targeted therapy in advanced lung adenocarcinomas
Jin, Y., Shi, X., Zhao, J., He, Q., Chen, M., Yan, J., Ou, Q., Wu, X., Shao, Y. W., & Yu, X. (2018) · Lung Cancer · doi:10.1016/j.lungcan.2018.07.039 · Cited by 61
Шао, Д., Lin, Y., Liu, J., Wan, L., Zu, L., Cheng, S., Fei, L., Deng, R., Wang, J. Z., Chen, X., et al. (2016) · Scientific Reports · doi:10.1038/srep22338 · Cited by 63
Guo, T., Ma, H., & Zhou, Y. (2019) · PeerJ · doi:10.7717/peerj.7313 · Cited by 64
Bone metastases in non-small cell lung cancer: a narrative review
Knapp, B. J., Devarakonda, S. H. K., & Govindan, R. (2022) · Journal of Thoracic Disease · doi:10.21037/jtd-21-1502 · Cited by 62
Schneider, F., Derrick, V., Davison, J. M., Strollo, D. C., Incharoen, P., & Đačić, S. (2016) · Modern Pathology · doi:10.1038/modpathol.2016.66 · Cited by 62
Schneeberger, V. E., Allaj, V., Gardner, E. E., Poirier, J. T., & Rudin, C. M. (2016) · PLoS ONE · doi:10.1371/journal.pone.0160587 · Cited by 62
Self-citationПавловна, В. Н., Rechsteiner, M., Wong, C. E., Zhong, Q., Rössle, M., Bode, B., Moch, H., Soltermann, A., Wild, P. J., & Tischler, V. (2016) · Cancer Cytopathology · doi:10.1002/cncy.21771 · Cited by 61
MicroRNA-365 promotes lung carcinogenesis by downregulating the USP33/SLIT2/ROBO1 signalling pathway
Wang, Y., Zhang, S., Bao, H., Mu, S., Zhang, B., Ma, H., & Ma, S. (2018) · Cancer Cell International · doi:10.1186/s12935-018-0563-6 · Cited by 61
Metadata
- Authors
- Kris, M. G., Johnson, B. E., Berry, L. D., Kwiatkowski, D. J., Iafrate, A. J., Wistuba, I. I., Varella-Garcia, M., Franklin, W. A., Aronson, S. L., Su, P.-F., Shyr, Y., Camidge, D. R., Sequist, L. V., Glisson, B. S., Khuri, F. R., Garon, E. B., Pao, W., Rudin, C., Schiller, J., Haura, E. B., Socinski, M., Shirai, K., Chen, H., Giaccone, G., Ladanyi, M., Kugler, K., Minna, J. D., & Bunn, P. A.
- Affiliations
- Memorial Sloan Kettering Cancer Center (US)
- Dana-Farber Cancer Institute (US)
- Vanderbilt University (US)
- Brigham and Women's Hospital (US)
- Massachusetts General Hospital (US)
- The University of Texas MD Anderson Cancer Center (US)
- University of Colorado Cancer Center Denver, Aurora
- University of Colorado Cancer Center (US)
- The Partners HealthCare Center for Personalized Genetic Medicine, Boston, Massachusetts
- Winship Cancer Institute (US)
- University of California, Los Angeles (US)
- Johns Hopkins University (US)
- The University of Texas Southwestern Medical Center (US)
- Moffitt Cancer Center (US)
- UPMC Hillman Cancer Center (US)
- Medical University of South Carolina (US)
- National Institutes of Health (US)
- Corresponding author
- Kris, Mark G.
- ORCID
- Kris, Mark G.
- Johnson, Bruce E.
- Berry, Lynne D.
- Kwiatkowski, David J.
- Iafrate, A. John
- Wistuba, Ignacio I.
- Shyr, Yu
- Camidge, D. Ross
- Sequist, Lecia V.
- Glisson, Bonnie S.
- Khuri, Fadlo R.
- Garon, Edward B.
- Pao, William
- Rudin, Charles
- Schiller, Joan
- Haura, Eric B.
- Socinski, Mark
- Shirai, Keisuke
- Chen, Heidi
- Giaccone, Giuseppe
- Ladanyi, Marc
- Minna, John D.
- Bunn, Paul A.
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2014-05-21
- Volume
- 311
- Issue
- 19
- Pages
- 1998
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- PMC
- PMC4163053
- OpenAlex
- W2065477010
- Semantic Scholar
- 07fff1c9d77fb2b8731d7d86b38c7ac05df654c7
- Cited by
- 1,724
- References
- 69
- Citations by year
- 2026: 55 · 2025: 99 · 2024: 101 · 2023: 116 · 2022: 164 · 2021: 171 · 2020: 173 · 2019: 137 · 2018: 186 · 2017: 162 · 2016: 173 · 2015: 146 · 2014: 37
- FWCI
- 138.25
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- JAMA (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (UL1TR000124)
- National Cancer Institute (RC2CA148394, K23CA149079, P01CA129243, 1RC2CA148394‐010, P50CA058187, P30CA008748, P30CA016672, P30CA046934)
- National Center for Advancing Translational Sciences
- Topics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Treatments and Mutations
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Diagnosis and Treatment
- Keywords
- lung adenocarcinoma, oncogenic drivers, targeted therapy, multiplex genotyping, KRAS, EGFR, ALK rearrangement, BRAF, PIK3CA, ERBB2, MET amplification, NRAS, MEK1, AKT1, metastatic lung cancer, survival, genotype-directed therapy, clinical trial recruitment
- MeSH terms
- Adenocarcinoma of Lung, Adenocarcinoma, Aged, Female, Genotype, Humans, Lung Neoplasms, Male, Middle Aged, Proto-Oncogenes, Survival Analysis, Sequence Analysis, DNA, Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization, Molecular Targeted Therapy, Multiplex Polymerase Chain Reaction
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-06, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-06 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
