Haywood K

Introduction: Advancements in genomic profiling now allow for routine comprehensive somatic genomic alteration testing in all patients with advanced cancer. A subset of patients will have targetable genomic alterations, though the frequency of these alterations and the efficacy of the matched treatments have varied amongst published data. Several commercially available platforms exist, but the ideal method to appropriately interpret and apply this data across various clinical tumor types and disease stages is still unclear.

Methods: We obtained a list of all the next generation sequencing (NGS) panels submitted from our center to the National Precision Oncology Program (NPOP). A total of 53 patients were included in the analysis. We analyzed the most frequently altered genes, the tumor types most frequently profiled, the frequency of cases with targetable alterations, and the efficacy of the matched treatments in individual patients. We also compared the number and types of alterations reported as well as the length of reports generated by the three different commercial NGS platforms used in our cohort.

Results: A total of 19/53 (35.8%) patients had targetable alterations. Five out of 21 (23.8%) received a targeted therapy. Non-small cell lung cancer [NSCLC] (n = 14; 26%) and prostate cancer (n=9; 17%) were the most frequently profiled tumors. In the NSCLC cohort, 7/14 (50%) had targetable alterations, including two patients in whom a prior single gene test for the specific alteration [EGFR, BRAF] was negative. NGS panels produced on average 6.6-13.0 alterations per patient, and average report length ranged from 8.3-19.0 pages.

Conclusions: NGS testing has been implemented by providers across a variety of tumor types at our institution, though the number of patients receiving matched treatments is low. Reflexive serial single-gene testing in NSCLC for EGFR, ALK, ROS1, and BRAF is likely reducing the number of NGS panels sent in these patients. Two false-negative single gene tests in our small cohort suggests we are underdiagnosing driver alterations in these patients with this approach. We would suggest exploring decision support tools and provider education in order to encourage judicious and clinically meaningful use of this valuable resource.

Introduction: Advancements in genomic profiling now allow for routine comprehensive somatic genomic alteration testing in all patients with advanced cancer. A subset of patients will have targetable genomic alterations, though the frequency of these alterations and the efficacy of the matched treatments have varied amongst published data. Several commercially available platforms exist, but the ideal method to appropriately interpret and apply this data across various clinical tumor types and disease stages is still unclear.

Methods: We obtained a list of all the next generation sequencing (NGS) panels submitted from our center to the National Precision Oncology Program (NPOP). A total of 53 patients were included in the analysis. We analyzed the most frequently altered genes, the tumor types most frequently profiled, the frequency of cases with targetable alterations, and the efficacy of the matched treatments in individual patients. We also compared the number and types of alterations reported as well as the length of reports generated by the three different commercial NGS platforms used in our cohort.

Results: A total of 19/53 (35.8%) patients had targetable alterations. Five out of 21 (23.8%) received a targeted therapy. Non-small cell lung cancer [NSCLC] (n = 14; 26%) and prostate cancer (n=9; 17%) were the most frequently profiled tumors. In the NSCLC cohort, 7/14 (50%) had targetable alterations, including two patients in whom a prior single gene test for the specific alteration [EGFR, BRAF] was negative. NGS panels produced on average 6.6-13.0 alterations per patient, and average report length ranged from 8.3-19.0 pages.

Conclusions: NGS testing has been implemented by providers across a variety of tumor types at our institution, though the number of patients receiving matched treatments is low. Reflexive serial single-gene testing in NSCLC for EGFR, ALK, ROS1, and BRAF is likely reducing the number of NGS panels sent in these patients. Two false-negative single gene tests in our small cohort suggests we are underdiagnosing driver alterations in these patients with this approach. We would suggest exploring decision support tools and provider education in order to encourage judicious and clinically meaningful use of this valuable resource.

Introduction: Advancements in genomic profiling now allow for routine comprehensive somatic genomic alteration testing in all patients with advanced cancer. A subset of patients will have targetable genomic alterations, though the frequency of these alterations and the efficacy of the matched treatments have varied amongst published data. Several commercially available platforms exist, but the ideal method to appropriately interpret and apply this data across various clinical tumor types and disease stages is still unclear.

Methods: We obtained a list of all the next generation sequencing (NGS) panels submitted from our center to the National Precision Oncology Program (NPOP). A total of 53 patients were included in the analysis. We analyzed the most frequently altered genes, the tumor types most frequently profiled, the frequency of cases with targetable alterations, and the efficacy of the matched treatments in individual patients. We also compared the number and types of alterations reported as well as the length of reports generated by the three different commercial NGS platforms used in our cohort.

Results: A total of 19/53 (35.8%) patients had targetable alterations. Five out of 21 (23.8%) received a targeted therapy. Non-small cell lung cancer [NSCLC] (n = 14; 26%) and prostate cancer (n=9; 17%) were the most frequently profiled tumors. In the NSCLC cohort, 7/14 (50%) had targetable alterations, including two patients in whom a prior single gene test for the specific alteration [EGFR, BRAF] was negative. NGS panels produced on average 6.6-13.0 alterations per patient, and average report length ranged from 8.3-19.0 pages.

Conclusions: NGS testing has been implemented by providers across a variety of tumor types at our institution, though the number of patients receiving matched treatments is low. Reflexive serial single-gene testing in NSCLC for EGFR, ALK, ROS1, and BRAF is likely reducing the number of NGS panels sent in these patients. Two false-negative single gene tests in our small cohort suggests we are underdiagnosing driver alterations in these patients with this approach. We would suggest exploring decision support tools and provider education in order to encourage judicious and clinically meaningful use of this valuable resource.

Purpose: To streamline the diagnostic evaluation of lung cancer.

Background: Lung cancer remains the leading cause of cancer death in the United States. Although more than half of cases present with metastatic disease, prognosis is still poor for earlier stage tumors. While most guidelines recommend a multidisciplinary approach to the diagnostic evaluation, recommendations and data for the timeliness of the process are lacking. Highly specialized diagnostic imaging tests and procedures are required to make the diagnosis, which can result in delays in the initiation of treatment. In the metastatic setting, the emergence of immunotherapies and targeted therapies requires additional tissue testing for predictive biomarkers and molecular alterations, increasing the importance of adequate biopsy specimens and tissue preservation. We reviewed the diagnostic evaluation process at our hospital in order to formulate a Plan, Do, Study, Act (PDSA) quality improvement project aimed at improving the efficiency of our process.

Methods: We performed a retrospective analysis of all cases of non-small cell lung cancer (NSCLC) diagnosed at the Birmingham VA Medical Center (BVAMC) from 2015-2017. Cases for which the entire evaluation was not performed at BVAMC were excluded. Outcomes of interest were time from imaging suggestive of lung cancer (T1) to pathologic diagnosis (T2) and to date of first treatment (T3).

Results: At the time of data submission, 171 cases had been analyzed. Mean time from suspicious imaging to pathologic diagnosis (T1-T2) was 59.5 days. Mean time from pathologic diagnosis to treatment initiation (T2-T3) was 69.4 days. Mean time spent in the diagnostic evaluation
(T1-T3) was 128.9 days. The data will be stratified further to identify opportunities for improvement. We have since instituted a multidisciplinary lung tumor board and are using CPRS-based tracking software to prospectively analyze cases and improve the efficiency of our process.

Conclusions: The diagnostic evaluation of lung cancer is a multi-step process, and unique factors contribute to delays at each step. It is essential to have a multidisciplinary team to help identify, predict and alleviate these barriers. Analysis of other variables including age, performance status, pulmonary function tests (PFTs), smoking, number of biopsies performed and utilization of positive emission tomography (PET) scans is underway.

Purpose: To streamline the diagnostic evaluation of lung cancer.

Background: Lung cancer remains the leading cause of cancer death in the United States. Although more than half of cases present with metastatic disease, prognosis is still poor for earlier stage tumors. While most guidelines recommend a multidisciplinary approach to the diagnostic evaluation, recommendations and data for the timeliness of the process are lacking. Highly specialized diagnostic imaging tests and procedures are required to make the diagnosis, which can result in delays in the initiation of treatment. In the metastatic setting, the emergence of immunotherapies and targeted therapies requires additional tissue testing for predictive biomarkers and molecular alterations, increasing the importance of adequate biopsy specimens and tissue preservation. We reviewed the diagnostic evaluation process at our hospital in order to formulate a Plan, Do, Study, Act (PDSA) quality improvement project aimed at improving the efficiency of our process.

Methods: We performed a retrospective analysis of all cases of non-small cell lung cancer (NSCLC) diagnosed at the Birmingham VA Medical Center (BVAMC) from 2015-2017. Cases for which the entire evaluation was not performed at BVAMC were excluded. Outcomes of interest were time from imaging suggestive of lung cancer (T1) to pathologic diagnosis (T2) and to date of first treatment (T3).

Results: At the time of data submission, 171 cases had been analyzed. Mean time from suspicious imaging to pathologic diagnosis (T1-T2) was 59.5 days. Mean time from pathologic diagnosis to treatment initiation (T2-T3) was 69.4 days. Mean time spent in the diagnostic evaluation
(T1-T3) was 128.9 days. The data will be stratified further to identify opportunities for improvement. We have since instituted a multidisciplinary lung tumor board and are using CPRS-based tracking software to prospectively analyze cases and improve the efficiency of our process.

Conclusions: The diagnostic evaluation of lung cancer is a multi-step process, and unique factors contribute to delays at each step. It is essential to have a multidisciplinary team to help identify, predict and alleviate these barriers. Analysis of other variables including age, performance status, pulmonary function tests (PFTs), smoking, number of biopsies performed and utilization of positive emission tomography (PET) scans is underway.

Purpose: To streamline the diagnostic evaluation of lung cancer.

Background: Lung cancer remains the leading cause of cancer death in the United States. Although more than half of cases present with metastatic disease, prognosis is still poor for earlier stage tumors. While most guidelines recommend a multidisciplinary approach to the diagnostic evaluation, recommendations and data for the timeliness of the process are lacking. Highly specialized diagnostic imaging tests and procedures are required to make the diagnosis, which can result in delays in the initiation of treatment. In the metastatic setting, the emergence of immunotherapies and targeted therapies requires additional tissue testing for predictive biomarkers and molecular alterations, increasing the importance of adequate biopsy specimens and tissue preservation. We reviewed the diagnostic evaluation process at our hospital in order to formulate a Plan, Do, Study, Act (PDSA) quality improvement project aimed at improving the efficiency of our process.

Methods: We performed a retrospective analysis of all cases of non-small cell lung cancer (NSCLC) diagnosed at the Birmingham VA Medical Center (BVAMC) from 2015-2017. Cases for which the entire evaluation was not performed at BVAMC were excluded. Outcomes of interest were time from imaging suggestive of lung cancer (T1) to pathologic diagnosis (T2) and to date of first treatment (T3).

Results: At the time of data submission, 171 cases had been analyzed. Mean time from suspicious imaging to pathologic diagnosis (T1-T2) was 59.5 days. Mean time from pathologic diagnosis to treatment initiation (T2-T3) was 69.4 days. Mean time spent in the diagnostic evaluation
(T1-T3) was 128.9 days. The data will be stratified further to identify opportunities for improvement. We have since instituted a multidisciplinary lung tumor board and are using CPRS-based tracking software to prospectively analyze cases and improve the efficiency of our process.

Conclusions: The diagnostic evaluation of lung cancer is a multi-step process, and unique factors contribute to delays at each step. It is essential to have a multidisciplinary team to help identify, predict and alleviate these barriers. Analysis of other variables including age, performance status, pulmonary function tests (PFTs), smoking, number of biopsies performed and utilization of positive emission tomography (PET) scans is underway.