Supplementary Figure 4. Serum concentration time profiles for AGS-16C3F(CHO) free cys-mcMMAF (data is presented as Mean {plus minus} SD)

Supplementary Figure 6. Serum concentration time profiles for AGS-16C3F(CHO) Total Antibody (TAb) (data is presented as Mean {plus minus} SD)

Supplementary Figure 2. Serum concentration time profiles for AGS-16C3F(CHO) antibody drug conjugate (ADC) (data is presented as Mean {plus minus} SD)

Supplementary Figure 1. Concentration time profiles for AGS-16M8F(Hyb) antibody drug conjugate (ADC) (data is presented as Mean {plus minus} SD)

Supplementary Figure 5. Serum concentration time profiles for AGS-16M8F(Hyb) Total Antibody (TAb) (data is presented as Mean {plus minus} SD)

Objectives Screening subjects for drug-drug interactions (DDIs) before enrollment in oncology clinical trials is integral to ensuring safety, but standard procedures or tools are not readily available to screen DDI in this setting. Our objectives were to develop a DDI screening tool for use during oncology clinical trial enrollment and to test usability in single-center and multicenter pilot studies. Methods A multistage approach was used for this quality improvement intervention. Semistructured interviews with individuals responsible for DDI screening were conducted to develop a prototype tool. The tool was used for screening DDI in subjects enrolling in National Clinical Trials Network trials of commercially available agents during a single-center 3-month pilot. Improvements were made, and a 3-month multicenter pilot was conducted at volunteer SWOG Cancer Research Network sites. Participants were surveyed to determine tool usability and efficiency. Results A tool was developed from semistructured interviews. A critical feature was reporting which medications had specific pharmacokinetic and pharmacodynamic characteristics including transporter and cytochrome P450 substrates, inhibitors, or inducers and QT prolongation. In the 12-site study, average (SD) DDI screening time for each patient decreased by 15.7 (10.2) minutes (range, 3-35 minutes; P < 0.001). Users reported the tool highly usable, with >90% agreeing with all positive usability characterizations and disagreeing with all negative complexity characterizations. Conclusions A DDI screening tool for oncology clinical trial enrollment was created and its usability confirmed. Further testing with more diverse investigator sites and study drugs during eligibility screening is warranted to improve safety and data accuracy within clinical trials.

Nearly half of all metastatic melanoma patients possess the BRAF V600 mutation. Several therapies are approved for advanced stage melanoma, but it is unclear if there is a differential outcome to various immunotherapy regimens based on BRAF mutation status. We retrospectively analyzed a cohort of metastatic or unresectable melanoma patients who were treated with combination ipilimumab/nivolumab (ipi/nivo) or anti-PD-1 monotherapy, nivolumab, or pembrolizumab, as first-line treatment. 235 previously untreated patients were identified in our study. Our univariate analysis showed no statistical difference in progression-free survival (PFS) or overall survival (OS) with ipi/nivo versus anti-PD-1 monotherapy in the BRAF V600 mutant cohort, but there was improved PFS [HR: 0.48, 95% CI, 0.28-0.80] and OS [HR: 0.50, 95% CI, 0.26-0.96] with ipi/nivo compared to anti-PD-1 monotherapy in the BRAF WT group. After adjusting for known prognostic variables in our multivariable analysis, the BRAF WT cohort continued to show PFS and OS benefit with ipi/nivo compared to anti-PD-1 monotherapy. Our single-institution analysis suggests ipi/nivo should be considered over anti-PD-1 monotherapy as the initial immunotherapy regimen for metastatic melanoma patients regardless of BRAF mutation status, but possibly with greater benefit in BRAF WT.

The NCCN Guidelines for Kidney Cancer provide multidisciplinary recommendations for the clinical management of patients with clear cell and non-clear cell renal cell carcinoma, and are intended to assist with clinical decision-making. These NCCN Guidelines Insights summarize the NCCN Kidney Cancer Panel discussions for the 2020 update to the guidelines regarding initial management and first-line systemic therapy options for patients with advanced clear cell renal cell carcinoma.

Abstract Background Endoglin is an essential angiogenic receptor expressed on proliferating tumor vessels and RCC stem cells that is implicated as a mechanism of VEGF resistance. TRC105 is an endoglin monoclonal antibody that potentiates the anti-tumor activity of VEGF inhibitors in preclinical models and demonstrated a 29% RECIST response rate when combined with AX in patients with mRCC in a Phase 1b trial. Methods TRAXAR was a multicenter, randomized 1:1 (stratified by ECOG, 0 vs. 1), Phase 2 study of TRAX vs AX in patients with mRCC who had progressed following one prior VEGF inhibitor at 33 centers in the US and EU. The primary endpoint was progression-free survival (PFS) assessed by RECIST by independent review committee (IRC). Secondary endpoints included overall response rate (ORR), and safety. PFS and ORR were also assessed by Investigator review (INV) and according to Choi criteria (CC). Results Of 150 pts (TRAX, 75; AX, 75), 106 (71%) were male, 142 (95%) were white; median age was 64 years (range, 38-82). Treatment with TRAX did not prolong PFS compared to AX. ORR was not different based on IRC, INV or CC (Table). Most all-grade common adverse events (AEs) in TRAX vs AX: headache (65.8% vs. 16.2%), epistaxis (63.0% vs. 8.1%), and diarrhea (60.3% vs. 59.5%); most common serious AEs included: anemia (6.9% vs. 1.4%) and dehydration (4.1% vs. 0%). Table . 912PD IRC INV CC TRAX AX TRAX AX TRAX AX Median PFS, mo (95% CI) 6.7 (5.6-13.1) 11.4 (5.8-NE) 7.2 (5.5-9.1) 7.4 (5.5-12.8) 7.2 (5.6-9.4) 7.5 (5.6-20.3) HR (95% CI) p-value 1.42 (0.88-2.30) 0.15 1.41 (0.95-2.10) 0.09 1.30 (0.83-2.03) 0.26 ORR, % 33.8 32.9 34.8 30.6 66.2 67.1 Odds ratio (95% CI) p-value 1.04 (0.50-2.15) 0.92 1.19 (0.58-2.44) 0.63 0.96 (0.47-1.96) 0.91 NE: not estimable; CI: confidence interval; mo: months Conclusions TRC105 did not demonstrate activity when combined with AX in patients with mRCC who had received prior VEGF inhibitor treatment, whether assessed using RECIST or Choi criteria. TRAX was generally well tolerated in pts with advanced or metastatic RCC. Clinical trial identification NCT01806064. Legal entity responsible for the study TRACON Pharmaceuticals. Funding TRACON Pharmaceuticals. Disclosure T.K. Choueiri: Advisory / Consultancy, Research grant / Funding (institution), Travel / Accommodation / Expenses: TRACON; Honoraria (institution), Advisory / Consultancy, Research grant / Funding (institution): AstraZeneca; Honoraria (institution), Advisory / Consultancy, Research grant / Funding (institution): Bayer; Honoraria (institution), Advisory / Consultancy, Research grant / Funding (institution): BMS; Honoraria (institution), Advisory / Consultancy, Research grant / Funding (institution): Cerulean; Honoraria (institution), Advisory / Consultancy, Research grant / Funding (institution): Eisai; Honoraria (institution), Advisory / Consultancy, Research grant / Funding (institution): Foundation Medicine; Honoraria (institution), Advisory / Consultancy, Research grant / Funding (institution): Exelixis; Honoraria (institution), Advisory / Consultancy, Research grant / Funding (institution): Ipsen; Honoraria (institution), Advisory / Consultancy, Research grant / Funding (institution): Genentech; Honoraria (institution), Advisory / Consultancy, Research grant / Funding (institution): Roche; Honoraria (institution), Advisory / Consultancy, Research grant / Funding (institution): Roche Products Limited; Honoraria (institution), Advisory / Consultancy, Research grant / Funding (institution): GSM; Honoraria (institution), Advisory / Consultancy, Research grant / Funding (institution): Merck; Honoraria (institution), Advisory / Consultancy, Research grant / Funding (institution): Novartis; Honoraria (institution), Advisory / Consultancy, Research grant / Funding (institution): Peloton; Honoraria (institution), Advisory / Consultancy, Research grant / Funding (institution): Pfizer; Honoraria (institution), Advisory / Consultancy, Research grant / Funding (institution): Prometheus; Honoraria (institution), Advisory / Consultancy, Research grant / Funding (institution): Corvus; Honoraria (institution): Calithera. R.K. Pachynski: Advisory / Consultancy: EMD Serono; Advisory / Consultancy: Bristol-Myers Squibb; Advisory / Consultancy: Pfizer; Advisory / Consultancy, Speaker Bureau / Expert testimony: Sanofi; Advisory / Consultancy: Jounce Therapeutics; Speaker Bureau / Expert testimony: Dendreon; Speaker Bureau / Expert testimony: Merck; Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: Genentech/Roche; Speaker Bureau / Expert testimony: Genomic Health; Advisory / Consultancy: Bayer. Y. Zakharia: Advisory / Consultancy: Amgen; Advisory / Consultancy: Roche; Advisory / Consultancy: Novartis; Advisory / Consultancy: Jansen; Advisory / Consultancy: Eisai; Advisory / Consultancy: Exelixis; Advisory / Consultancy: Castle Bioscience; Advisory / Consultancy: Pfizer; Advisory / Consultancy: Array. T.H. Ho: Advisory / Consultancy: Roche; Advisory / Consultancy: Pfizer; Advisory / Consultancy: ipensenlivemeetings; Advisory / Consultancy: cardinal health; Advisory / Consultancy: Exelixis. B.E. Simpson: Shareholder / Stockholder / Stock options, Full / Part-time employment: TRACON Pharmaceuticals. B. Adams: Shareholder / Stockholder / Stock options, Full / Part-time employment: TRACON. L. Robertson: Shareholder / Stockholder / Stock options, Full / Part-time employment: TRACON. M. Darif: Advisory / Consultancy: TRACON. C. Theuer: Shareholder / Stockholder / Stock options, Full / Part-time employment, Officer / Board of Directors: TRACON. N. Agarwal: Advisory / Consultancy: Astellas; Advisory / Consultancy, Research grant / Funding (self): AstraZeneca; Advisory / Consultancy: Argos; Advisory / Consultancy: Bayer; Advisory / Consultancy: Clovis; Advisory / Consultancy, Research grant / Funding (self): Eisai; Advisory / Consultancy, Research grant / Funding (self): Exelixis; Advisory / Consultancy: EMD Serono; Advisory / Consultancy, Research grant / Funding (self): Ely Lilly; Advisory / Consultancy: Foundation One; Advisory / Consultancy: Genentech; Advisory / Consultancy, Research grant / Funding (self): Janssen; Advisory / Consultancy, Research grant / Funding (self): Merck; Advisory / Consultancy: Medivation; Advisory / Consultancy, Research grant / Funding (self): Novartis; Advisory / Consultancy: Nektar; Advisory / Consultancy, Research grant / Funding (self): Pfizer; Advisory / Consultancy: Pharmacyclics; Research grant / Funding (institution): Bavarian Nordic; Research grant / Funding (self): TRACON. All other authors have declared no conflicts of interest.

The NCCN Guidelines for Kidney Cancer provide multidisciplinary recommendations for the clinical management of patients with clear cell and non-clear cell renal cell carcinoma, and are intended to assist with clinical decision-making. These NCCN Guidelines Insights summarize the NCCN Kidney Cancer Panel discussions for the 2020 update to the guidelines regarding initial management and first-line systemic therapy options for patients with advanced clear cell renal cell carcinoma.

e18819 Background: Oncology patients are at high risk of clinically relevant drug-drug interactions (DDIs) due to high rates of polypharmacy. DDIs in patients enrolled in clinical trials can adversely affect patient safety, study drug outcomes and validity. The study objective was to determine the prevalence of clinically relevant DDIs involving study drugs in patients enrolled in NCTN clinical trials at the University of Michigan Comprehensive Cancer Center (UMCCC). Methods: All patients enrolled in NCTN trials of commercially available medications at UMCCC from January 2013 to August 2017 were included. Patient’s concomitant medication lists at the enrollment date, or at the next available date, were collected from UMCCC electronic medical records. Medication lists were screened using Lexicomp, and all major/contraindicated (level D or X) DDIs involving study agents were recorded. Flagged interactions were reviewed by a pharmacist and PharmD student for clinical relevance. Discordant decisions were discussed until reaching consensus. A clinically relevant interaction was defined as a DDI that would warrant a medication change to ensure patient safety at enrollment. Results: One hundred thirty patients enrolled in 35 NCTN trials were included. Patients were taking 6.7 concomitant medications on average (median: 6, range: 0-21). Lexicomp detected at least one level D or X DDI in 23.8% of patients (31/130). Ten percent of all patients (13/130) had at least one clinically relevant DDI, and of the patients with clinically relevant DDI 46.2% (6/13) had DDI that affected the safety or efficacy of the study agent. Conclusions: These findings confirm a high prevalence of clinically relevant DDI involving study agents in patents enrolled in NCTN trials. More consistent and stringent DDI screening is needed during enrollment to reduce DDI prevalence to enhance patient safety and clinical trial data validity. Additionally, emphasis should be placed on DDI screening for trials likely to have DDI, such as if study drugs are strong inhibitors or inducers of CYP450 enzymes.

315 Background: Screening drug-drug interactions (DDI) for subjects enrolling in oncology clinical trials is critical to ensuring patient safety and the validity of clinical trial data. We previously reported that DDI screening is not uniformly conducted when screening patients for enrollment into SWOG clinical trials and found that at the University of Michigan Rogel Cancer Center up to 24.2% of subjects enrolled in National Clinical Trial Network (NCTN) trials had a DDI. Screening tools aid in DDI reduction in clinical practice, but none have been created for clinical trial enrollment. Our objective was to develop a clinical trial specific DDI screening tool based on features requested by the end-users of the tool at U-M. Methods: Semi-structured and informal interviews were conducted with all data managers who enroll patients into NCTN clinical trials at the U-M cancer center. Data managers were asked about their current workflow and desired features of a DDI screening tool. Responses were combined and reviewed for feasibility. Desired features were conveyed to PEPID, LLC (Phoenix, AZ) for tool development. Results: Four data managers were interviewed. Protocol-guided screening was a key workflow feature, which was completed by gathering DDI information primarily from the exclusion criteria and drug information sections of each respective protocol, Google, CredibleMeds, and the Indiana University P450 Drug Interaction Table. Consequently, a critical feature was the display of drug characteristics with wording that aligned with that in the protocol including transporter and CYP450 substrates, inhibitors, or inducers and QT prolongation potential. Additional desirable features included separate entry of study and concomitant drugs, filtering to display only DDI with study drugs, and PDF export of results. PEPID developed a prototype tool including these desired attributes for a prospective implementation pilot study. Conclusions: A first generation clinical trial specific DDI screening tool was developed based on end-user feedback. We are designing a prospective study to determine whether implementation of this tool can reduce DDI, enhance patient safety, and ensure validity of clinical trial data.

Abstract Purpose: To determine the safety, pharmacokinetics, and recommended phase II dose of an antibody–drug conjugate (ADC) targeting ectonucleotide phosphodiesterases-pyrophosphatase 3 (ENPP3) conjugated to monomethyl auristatin F (MMAF) in subjects with advanced metastatic renal cell carcinoma (mRCC). Patients and Methods: Two phase I studies were conducted sequentially with 2 ADCs considered equivalent, hybridoma-derived AGS-16M8F and Chinese hamster ovary–derived AGS-16C3F. AGS-16M8F was administered intravenously every 3 weeks at 5 dose levels ranging from 0.6 to 4.8 mg/kg until unacceptable toxicity or progression. The study was terminated before reaching the MTD. A second study with AGS-16C3F started with the AGS-16M8F bridging dose of 4.8 mg/kg given every 3 weeks. Results: The AGS-16M8F study (n = 26) closed before reaching the MTD. The median duration of treatment was 12 weeks (1.7–83 weeks). One subject had durable partial response (PR; 83 weeks) and 1 subject had prolonged stable disease (48 weeks). In the AGS-16C3F study (n = 34), the protocol-defined MTD was 3.6 mg/kg, but this was not tolerated in multiple doses. Reversible keratopathy was dose limiting and required multiple dose deescalations. The 1.8 mg/kg dose was determined to be safe and was associated with clinically relevant signs of antitumor response. Three of 13 subjects at 1.8 mg/kg had durable PRs (range, 100–143 weeks). Eight subjects at 2.7 mg/kg and 1.8 mg/kg had disease control >37 weeks (37.5–141 weeks). Conclusions: AGS-16C3F was tolerated and had durable antitumor activity at 1.8 mg/kg every 3 weeks. Clin Cancer Res; 24(18); 4399–406. ©2018 AACR.

BACKGROUND:Drug-drug interactions (DDIs) in subjects enrolling in clinical trials can impact not only safety of the patient but also study drug outcomes and data validity. This makes it critical to adequately screen and manage DDIs. The study objective was to determine the prevalence of DDIs involving study medications in subjects enrolling in National Clinical Trials Network (NCTN) clinical trials at a single institution. DDIs were evaluated based on study protocol recommendations for concomitant medication use (i.e. exclude, avoid or use caution), screening via DDI tool, and pharmacist review.METHODS:Subjects enrolled in NCTN trials of commercially available agents between January 2013 and August 2017 were included if a complete medication list was available. Complete medication lists were collected from the date of enrollment or the next available date then screened utilizing protocol guidance and the DDI screening tool, Lexicomp® Drug Interactions (Wolters Kluwer, Hudson, OH). Interactions were reviewed for clinical relevance: defined as a DDI that would require a medication change to ensure study agent safety and efficacy at enrollment.RESULTS:One hundred and twenty-eight subjects enrolled in 35 clinical trials were included. Protocol guidance detected 15 unique DDI pairs that should be avoided or used with caution in 10.2% (13/128) of subjects. The majority of these subjects did not have a clinically relevant DDI (69.2%, 9/13) based on pharmacist review. Lexicomp® detected moderate to major DDIs in 24.2% (31/128) of subjects, with 9.4% (12/128) having a clinically relevant DDI.CONCLUSIONS:This study confirms a high prevalence of DDIs present in subjects enrolling in oncology clinical trials. Further efforts should be made to improve methods to detect and manage DDIs in patients enrolling on clinical trials to ensure patient safety and trial data validity.

The NCCN Guidelines for Kidney Cancer provide multidisciplinary recommendations for the clinical management of patients with clear cell and non-clear cell renal carcinoma. These guidelines are developed by a multidisciplinary panel of leading experts from NCCN Member Institutions consisting of medical oncologists, hematologists and hematologic oncologists, radiation oncologists, urologists, and pathologists. The NCCN Guidelines are in continuous evolution and are updated annually or sometimes more often, if new high-quality clinical data become available in the interim.

Rationale and Objectives: To explore whether the sarcopenia body type can help predict response to interleukin-2 (IL-2) therapy in metastatic renal cell carcinoma (RCC).Materials and Methods: Institutional review board approval was obtained for this Health Insurance Portability and Accountability Act compliant retrospective cohort study of 75 subjects with metastatic RCC who underwent pretreatment contrast-enhanced computed tomography within 1 year of initiating IL-2 therapy. Cross-sectional area and attenuation of normal-density (31-100 Hounsfield units [HU]) and low-density (0-30 HU) dorsal muscles were obtained at the T11 vertebral level. The primary outcome was partial or complete response to IL-2 using RECIST 1.1 criteria at 6 weeks. A conditional inference tree was used to determine an optimal HU cutoff for predicting outcome. Bonferroni-adjusted multivariate logistic regression was conducted to investigate the independent associations between imaging features and response after controlling for demographics, doses of IL-2, and RCC prognostic scales (eg, Heng and the Memorial Sloan Kettering Cancer Center [MSKCC]).Results: Most subjects had intermediate prognosis by Heng (65% [49 of 75]) and the MSKCC (63% [47 of 75]) criteria; 7% had complete response and 12% had partial response. Mean attenuation of low-density dorsal muscles was a significant univariate predictor of IL-2 response after Bonferroni correction (P = 0.03). The odds of responding to treatment were 5.8 times higher for subjects with higher-attenuation low-density dorsal muscles (optimal cutoff: 18.1 HU). This persisted in multivariate analysis (P = 0.02). Body mass index (P = 0.67) and the Heng (P = 0.22) and MSKCC (P = 0.08) clinical prognostic scales were not significant predictors of response.Conclusions: Mean cross-sectional attenuation of low-density dorsal muscles (ie, sarcopenia) may predict IL-2 response in metastatic RCC. Clinical variables are poor predictors of response.

DESIGN, SETTING, AND PARTICIPANTS Subgroup analysis of a blinded, randomized, multicenter, phase 2 dose-ranging trial initiated May 31, 2011, including patients with clear-cell mRCC previously treated with antiangiogenic therapy. Data cutoffs for this subgroup analysis were May 15, 2013, for progression-free survival and objective response rate and March 5, 2014, for overall survival and duration of response. In this analysis, patients treated beyond first progression received their last dose of nivolumab more than 6 weeks after RECIST-defined progression, and patients not treated beyond first progression discontinued nivolumab before or at RECIST-defined progression.

Additional Contributions: Paul R. Yarnold, PhD, South Carolina College of Pharmacy, University of South Carolina, provided statistical support; Eleassa van Slooten, BA, Alyssa Trenery, BA, Alanna Murday, BA, Ashlyn Byrne, BA, and Matthew Bialkowski, BA, South Carolina College of Pharmacy, University of South Carolina, provided assistance with the literature review and data abstraction; and Dennis Raisch, PhD, University of New Mexico College of Pharmacy, University of New Mexico, Laura Bobolts, PharmD, Nova University and Oncology Analytics, Inc, Gowtham Rao, MD, PhD, MPH, Raja Fayad, MD, Arnold School of Public Health, University of South Carolina, and Bryan Chen, PhD, JD, LeAnn Norris, PharmD, Kevin Lu, PhD, Richard Schulz, PhD, Paul Ray, DO, MA, Virginia Noxon, MS, Michael Wyatt, MD, Sam Kessler, BA, and John Bian, PhD, South Carolina College of Pharmacy, University of South Carolina, provided assistance with writing the first draft. van Slooten, Trenery, Byrne, Bialkowski, and Kessler were compensated for their contributions; all other contributors were not compensated.

High tumor burden (TB) in pts with RCC is associated with poor prognosis (Iacovelli BJU Int 2012). In the Phase 3 METEOR trial (NCT01865747) in advanced RCC after prior vascular endothelial growth factor receptor (VEGFR) tyrosine kinase inhibitor (TKI) therapy (Choueiri NEJM 2015/ASCO 2016 abstr 4506), cabo significantly improved progression-free survival (PFS; HR 0.58, 95% CI 0.45–0.74; P < 0.0001), overall survival (OS; HR 0.66, 95% CI 0.53-0.83, P = 0.0003) and objective response rate (ORR; 17% vs 3%; P < 0.0001) compared with eve. 658 pts were randomized 1:1 to cabo (60 mg qd) or eve (10 mg qd). Stratification factors were MSKCC risk group and number of prior VEGFR TKIs. Endpoints included PFS, OS and ORR. Subgroup analyses by metastatic site and low and high TB (< median and ≥ median sum of target lesion diameters [SoD] at baseline) are presented. At baseline, 74% of pts had visceral (lung or liver) metastases (mets); 63% had lung mets and 29% had liver mets. Median SoD at baseline was 65 mm (range 0–291) in the cabo arm and 65 mm (0–258) in the eve arm. Subgroups by metastatic site and TB generally had similar baseline characteristics on both arms. High compared to low TB was associated with fewer favorable (34% vs 57%) and more intermediate (47% vs 36%) and poor risk (19% vs 7%) pts per MSKCC criteria. For pts with visceral mets, the HRs favored cabo (PFS HR 0.48, 95% CI 0.38–0.60; OS HR 0.66, 95% CI 0.52–0.85). These benefits with cabo were consistent across the metastatic sites analyzed (liver and lung). For pts with low TB, HRs for cabo vs eve were 0.63 (95% CI 0.47–0.84) for PFS and 0.76 (95% CI 0.54–1.08) for OS vs 0.41 (95% CI 0.31–0.54) for PFS and 0.60 (95% CI 0.45–0.80) for OS for pts with high TB. Median OS with cabo was 22.0 mo for low TB and 18.1 mo for high TB pts vs 19.3 mo and 12.2 mo with eve, respectively. The most common grade 3 or 4 adverse events in these subgroups were consistent with the safety profile in the overall study population. Treatment with cabo was associated with improved PFS and OS compared to eve in pts irrespective of tumor burden or metastatic sites. Pts with high tumor burden appeared to have a stronger relative benefit with cabo compared to eve for both OS and PFS.

The NCCN Guidelines for Kidney Cancer provide multidisciplinary recommendations for the clinical management of patients with clear cell and non-clear cell renal carcinoma. These NCCN Guidelines Insights highlight the recent updates/changes in these guidelines, and updates include axitinib as first-line treatment option for patients with clear cell renal carcinoma, new data to support pazopanib as subsequent therapy for patients with clear cell carcinoma after first-line treatment with another tyrosine kinase inhibitor, and guidelines for follow-up of patients with renal cell carcinoma.