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Objective to examine the geographic distribution of gynecologic oncologists (GO) and assess if the GO workforce is meeting the demand for oncology services for patients with gynecologic cancers. Methods We identified GO by National Provider Identifiers (NPI) and calculated county-level density of GO. County-level gynecologic cancer rates were derived from the U.S. Cancer Statistics to represent demand for GO services. A spatial data plot compared GO workforce to gynecologic cancer service demand. U.S. census county-level demographic information was collected and compared. Results In 2019, 1527 GO had a registered NPI. Of 3142 counties in the US, 2864 (91.2%) counties had no GO in their local county and 1943 (61.8%) counties had no GO in local or adjacent (neighboring) counties. As the gynecologic cancer rate increases (described in quintiles) in counties, there are fewer counties without a GO or adjacent GO. However, county-level GO density (number of GO per 100,000 women) did not significantly increase as the county-level incidence of gynecologic cancer increased (r = −0.12, p = 0.06)… Women living in counties with the highest gynecologic cancer rates and without access to a GO were more likely to reside in a rural area where residents had a lower median income and were predominately of White race.. Conclusion There are a significant number of counties in the U.S. without a GO. As county-level gynecologic cancer incidence increased, the proportion of counties without a GO decreased; GO density did not increase with increasing cancer rates. Rural counties with high gynecologic incidence rates are underserved by GO. This information can inform initiatives to improve outreach and collaboration to better meet the needs of patients in different geographic areas.

To date, the economic burden and patient-reported outcomes associated with carcinoid syndrome (CS) in patients with neuroendocrine tumor (NET) remain largely unknown. The objective of this study was to perform a systematic review of economic and quality-of-life (QOL) studies related to the treatment of CS. Articles included in the review were extracted from PubMed, Embase, and the Cochrane Library. Studies had to be in English and published between 1 January 2000 and 2 July 2020. Other study eligibility criteria included patients with NET with CS receiving treatment for CS, study outcomes of cost or QOL, and clinical trials or population-based studies using claims or other secondary databases. The interventions included somatostatin analogs, telotristat ethyl, or other treatment for CS. To evaluate the quality and bias of the included studies, the 24-item CHEERS and 10-item Gill and Feinstein checklists were used. We report a narrative synthesis of the findings from the selected studies. A total of 12 economic and 12 QOL studies met the inclusion criteria and were included for review. Patients with uncontrolled CS symptoms had 23–92% higher costs than those with controlled CS; mostly, ambulatory/outpatient services were the primary drivers of the costs. The use of telotristat ethyl may be cost effective if the societal willingness to pay is as high as $US150,000 per quality-adjusted life-year in the USA. Of the 12 QOL papers, only three case–control studies assessed QOL at baseline and more than two follow-up time points. Seven studies evaluated QOL at two or more time points but lacked a control group, obscuring direct intervention effects on patients’ well-being. We observed wide variations in the reviewed studies evaluating the economic burden and patient-reported outcomes, in terms of cost and QOL, of patients with CS. Although QOL is consistently impaired and costs are consistently increased by CS, the numbers of both cost and QOL studies among this patient population remain sparse, and many of the existing studies indicated an important need for quality improvement.

Introduction: BI-RADS category 4 is associated with a wide variability in probability of malignancy, ranging from 2 to 95% while biopsy-derived positive predictive value (PPV3) for this category’s lesions remains low at 21.1% in the US. A major fallout of these facts is that we have way very high false positive rate leading to too many unnecessary biopsies and their associated costs and emotional burden. We improved our in-house intelligent-augmented Breast cancer RISK calculator (iBRISK), an integrated deep learning (DL) based decision support app and assessed its performance in a multicenter IRB-approved study. Methods: We improved iBRISK by retraining the DL model with an expanded dataset of 9,700 patient records of clinical risk-factors and mammographic descriptors from Houston Methodist Hospital (HMH) and validated using another 1,078 patient records. These patients were all seen between March 2006 and December 2016. We assessed the model using blinded, independent retrospective BI-RADS 4 patients who had biopsies subsequently after mammography and seen January 2015 - June 2019 at three major healthcare institutions in Texas, USA: MD Anderson Cancer Center, the University of Texas Health Sciences Center at San Antonio, and HMH. We dichotomized and trichotomized the data to evaluate precision of risk stratification and probability of malignancy (POM) estimation translated into biopsy decision augmentation. The iBRISK score as a continuous predictor of malignancy and possible cost savings was also analyzed. Results: The multicenter validation dataset had 4,209 women, median age (interquartile) was 56 (45, 65) years. The use of iBRISK score as a continuous predictor of malignancy yielded an AUC of 0.97. Among “low” and “moderate” POM patients, only two out of 1,228 patients (0.16%) and 118 out of 1788 (6.6%) were malignant respectively. This translates to an even better precision when compared to newly introduced BI-RADS 4 subcategories 4A and 4B, with associated PPV3s of 7.6% and 22%, respectively. The “high” POM group had a malignancy rate of 85.9% (1,025/1,193). Estimated potential cost savings in the US was over $260 million. Conclusion: The iBRISK app demonstrated high sensitivity in malignancy prediction and can potentially be used to safely obviate biopsies in up to 50% of patients in low/moderate POM-groups. This would result in significant healthcare quality improvement, cost savings, and help reduce patient anxiety. Citation Format: Chika F. Ezeana, Tiancheng He, Tejal A. Patel, Virginia Kaklamani, Maryam Elmi, Erica Ibarra, Pamela M. Otto, Kenneth A. Kist, Heather Speck, Lin Wang, Joe Ensor, Ya-Chen T. Shih, Bumyang Kim, I-Wen Pan, David Spak, Wei T. Yang, Jenny C. Chang, Stephen T. Wong. A multicenter study validated an integrated deep learning model for precision malignancy risk assessment and reducing unnecessary biopsies in BI-RADS 4 cases. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5698.

PURPOSE: To examine the geographic distribution of physician and pharmacist workforce specialized in oncology in the United States. METHODS: Using the National Provider Identifier data, we identified two types of oncology workforce via the healthcare provider taxonomy codes. Oncologists were physicians self-identified as providing oncologic care to patients. Oncology pharmacists were pharmacists with an oncology subspecialty. We calculated the geographic density of physician and pharmacist oncology workforce and used county-level cancer crude rates to quantify the demand for oncology workforce. We used spatial data to plot the density of oncology workforces relative to county-level cancer rates and compared the county-level density of oncologists and oncology pharmacists. RESULTS: Of the 30,553 members of the oncology workforce in 2019, 28,681 were oncologists and 1,090 were oncology pharmacists. The mean county-level density of oncologists was 2.94 (SD = 7.32) per 100,000 persons. Sixty-four percent of counties had no oncologists with primary practice location in that county and 12% had no oncologists in the local and adjacent counties. Counties in the top quartile of cancer rates had the highest percentage without any oncologists with primary practice location in the county (75%) and with no oncologists in the local as well as adjacent counties (16%). CONCLUSION: Geographically mismatched demand and supply characterized the current oncology workforce. Wide discrepancies in the supply of oncologists across geographic regions highlight the importance of developing core competencies for health professions not specialized in oncology to deliver quality cancer care in areas with unmet need for oncology care.

Little is known about how screening facilities are meeting the requirements for the reimbursement of lung cancer screening from the Centers for MedicareMedicaid Services (CMS), including 1) the collection and submission of data to the CMS-approved registry (American College of Radiology [ACR] Lung Cancer Screening Registry), 2) the verification of a counseling and shared decision-making (SDM) visit having occurred as part of the written order for lung cancer screening with low-dose computed tomography, and 3) the offering of smoking cessation interventions.The authors identified facilities in a southwestern state that were listed by either the ACR Lung Cancer Screening Registry or the GO2 Foundation Centers of Excellence. To select facilities, they used 2 purposive sampling approaches: maximum variation sampling and snowball sampling. They surveyed facilities from February to November 2019.There were 87 facilities contacted, and a total of 63 facilities representing 32 counties across Texas completed the survey. Nearly all facilities used Lung-RADS to classify nodules (92%; n = 58) and submitted data to a CMS-approved registry (92%; n = 57). Most facilities verified that the counseling and SDM visit had occurred (86%; n = 54). Although slightly more than half of the facilities reported always providing self-help cessation materials (68%; n = 42), similar or higher proportions of facilities reported that they never referred smokers to onsite cessation services (68%; n = 42) or quitlines (77%; n = 47), provided cessation counseling (81%; n = 50), or recommended medications (85%; n = 52).In general, screening facilities are meeting CMS requirements for screening, but they are struggling to offer smoking cessation interventions other than providing self-help materials.

We previously reported a significant volume–outcome relationship in mortality rates after gastrectomies for gastric cancer patients in Texas (1999–2001). We aimed to identify whether changes in the volume distribution of gastrectomies occurred, whether volume–outcome relationships persisted, and potential changes in the factors influencing volume–outcome relationships. We performed a population-based study using the Texas Inpatient Public Use Data File between 2010 and 2015. Hospitals were classified as high-volume centers (HVCs, > 15 cases per year), intermediate-volume centers (IVCs, 3–15 cases per year), and low-volume centers (LVCs

Clinical practice guidelines for treating tobacco use and lung cancer screening guidelines recommend smoking cessation counseling to current smokers by health care professionals. Our objective was to determine the contemporary patterns of current smokers’ discussions about smoking with their health care professionals in the USA. We conducted an observational study of 30,132 current smokers (weighted sample 40,126,006) for the years 2011 to 2015 using data from the National Health Interview Survey. Our main outcome was the proportion of current smokers who had discussions about smoking with their health care professionals. We used the Cochran-Armitage trend test to evaluate the temporal trends in current smokers’ discussions about smoking, and used a multivariable logistic model to determine the predictors of discussions about smoking, controlling for smokers’ demographics, health status, and receipts of lung cancer screening. Our study found the proportion of current smokers who had discussions about smoking with their health care professionals increased from 51.3% in 2011 to 55.4% in 2015 (P-trend

The economic burden of renal cell carcinoma (RCC) came into sharp focus when the UK National Institute for Health and Clinical Excellence (NICE) denied coverage (later reversed) of sunitinib for metastatic RCC. In the first of two articles that provide updated reviews and analyses of the economic burden of RCC, we conducted an updated literature review of RCC-related economic studies. We performed a literature search of PubMed, EMBASE and the Cochrane Library for English-language studies published from 1 January 2000 to 15 June 2010. We also performed a separate search for related studies in the Health Technology Assessment (HTA) reports published by the National Institute for Health Research HTA Programme in the UK. Identified articles were classified into three categories: cost studies, cost-effectiveness/cost-utility studies and cost-of-illness studies. All cost estimates were normalized to $US, year 2009 values. We identified 20 articles, including six cost, six cost-utility and eight cost-of-illness studies. In general, the studies found new surgical techniques, such as laparoscopic partial nephrectomy, to be potentially cost saving (in the range of $US181-5842). Targeted agents, such as bevacizumab, sunitinib, sorafenib and temsirolimus, were associated with higher lifetime costs ($US8537-72 254) and were not always considered to be cost effective by authors of the cost-effectiveness studies included in this review (incremental cost-effectiveness ratio [ICER]: $US49 959-272 418 per QALY). The literature reported annual estimates of the US economic burden of RCC between $US0.60 billion and $US5.19 billion, with per-patient costs of $US16 488-43 805. RCC is associated with substantial economic burden, although the estimates are wide ranging. Comparisons of the estimates across studies were hindered by variations in study methodology, choice of database and the associated timeframe, and limitations inherent to each database. More research is needed to assess the quality of the economic studies of RCC and to understand why the estimated costs differ across studies.

Background There are few data to support the use of varying imaging modalities in evaluating recurrence in non–small-cell lung cancer (NSCLC). We compared the efficacy of surveillance positron emission tomography (PET)/computed tomography (CT) versus CT scans of the chest in detecting recurrences after definitive radiation for NSCLC. Materials and Methods We retrospectively analyzed 200 patients treated between 2000 and 2011 who met the inclusion criteria of stage III NSCLC, completion of definitive radiation treatment, and absence of recurrence within the initial 6 months. These patients were then grouped on the basis of the use of PET/CT imaging during postradiation surveillance. Patients who received ≥ 1 PET/CT scans within 6 months of the end of radiation treatment were placed in the PET group whereas all others were placed in the CT group. We compared survival times from the end of treatment to the date of death or last follow-up using log rank tests. Multivariate analysis was conducted to identify factors associated with decreased survival. Results In the entire cohort, median event-free survival (EFS) was 26.7 months, and median overall survival (OS) was 41.2 months. The CT group had a median EFS of 21.4 months versus 29.4 months for the PET group ( P = .59). There was no difference in OS between the CT and PET groups (median OS of 41.2 and 41.3 months, respectively; P = .59). There was also no difference in local recurrence-free survival or distant metastases-free survival between the CT-only and PET/CT groups ( P = .92 and P = .30, respectively). Similarly, in multivariate analysis, stratification into the PET group was not associated with improved EFS (hazard ratio [HR], 0.90; 95% confidence interval [CI], 0.61-1.34; P = .60) or OS (HR, 1.2; 95% CI, 0.83-1.7; P = .34). Conclusions In stage III NSCLC patients treated with definitive radiation and without early recurrence, PET/CT scan surveillance did not result in decreased time to detection of locoregional or distant recurrence or improved survival.

Pseudoprogression has been observed in patients with various tumor types treated with immunotherapy. However, the frequency of pseudoprogression is unknown in gastrointestinal malignancies. Metastatic colorectal cancer (mCRC) and advanced pancreatic ductal adenocarcinoma (PDAC) patients who progressed on treatment with immunotherapy beyond RECIST version 1.1 criteria were analyzed. Degree of progression, tumor markers, time to progression, overall survival, Eastern Cooperative Oncology Group Performance Status (ECOG PS), and costs were analyzed for patients treated beyond progression (TBP) and not treated beyond progression. Fifty-nine of 159 (37%) patients with mCRC or PDAC were TBP (31 mCRC, 28 PDAC). Fifty-four of 59 (92%) patients were microsatellite stable. Zero of these 59 patients with initial treatment beyond progression demonstrated subsequent radiographic tumor shrinkage at a median 42 days from first scan documenting progression. A pseudoprogression rate of >6% could be excluded with 95% confidence. Compared with baseline, median growth on the first and second scan that showed progression was 29.8% and 43%, respectively. In those not treated beyond progression, median growth at first restaging was 31.2%. The trend in change in tumor size positively correlated with the trend in tumor markers in all patients TBP. Fifteen patients (25%) experienced grade 3/4 adverse events by continuing treatment beyond progression, whereas 19 (32%) experienced deterioration in ECOG PS. Pseudoprogression was not seen in microsatellite stable patients with mCRC or PDAC treated with immunotherapy. Changes in tumor markers correlated with changes in tumor volume. This data may help inform future treatment decisions and/or trial design in patients with mCRC or advanced PDAC treated with immunotherapy.

Purpose The Texas Breast and Cervical Cancer Services (BCCS) program was established to address socioeconomic disparities in breast and cervical cancer screening and survival. This study examined the impact of the program on treatment and survival of breast cancer patients. Methods A retrospective analysis was performed using the Texas Cancer Registry data linked to the BCCS program data. The sample consisted of 40- to 64-year-old women screened and diagnosed with breast cancer through the BCCS program (participants) and similar women living in low socioeconomic status census tracts and diagnosed outside the program (comparison group) during 1995-2008. Regular screeners among the participants were also compared with the comparison group. Results Participants had lower rates of breast surgery and higher rates of chemotherapy as compared with the comparison group. Participants undergoing surgery had higher rates of mastectomy (as compared with breast-conserving surgery) and lower rates of adjuvant radiation therapy. Unadjusted survival rates were similar between the participants and the comparison group, and higher among regular screeners, which was primarily driven by stage at diagnosis. Adjusted survival rates were similar between the 3 groups. Conclusions Although there are differences in the types of treatment provided to the participants and the comparison group, there is no evidence of guideline noncompliance or stage-inappropriate treatment provision in either of the groups. Despite being diagnosed with a more advanced stage, the participants had similar unadjusted and adjusted survival rates as the comparison group. Access to timely treatment improved survival and brought the underserved participants on par with the comparison group.

We estimated and compared the costs of positron emission tomography (PET)/computed tomography (CT) versus CT for surveillance of patients with stage III non–small-cell lung cancer and identified patient and provider demographic characteristics associated with preference for PET/CT. PET/CT was associated with higher costs for 18 months post-treatment, but the difference was borderline statistically significant at 24 months. Consistent with national guidelines, PET/CT surveillance was not cost-saving and did not provide an economic benefit over CT. INTRODUCTION: A previous study showed that use of positron emission tomography (PET)/computed tomography (CT) for surveillance after treatment of non–small-cell lung cancer (NSCLC) does not yield a detection or survival benefit over the use of chest CT. However, PET/CT remains a common method of follow-up imaging. Here we estimated and compared the costs of PET/CT versus CT for surveillance of patients with stage III NSCLC and identified patient and provider demographic characteristics associated with preference for use of PET/CT. PATIENTS AND METHODS: We reviewed 178 patients with stage III NSCLC who had received ≥ 1 PET/CT scan within 6 months of completing radiotherapy (n = 89) or had received CT after radiotherapy (n = 89) from 2000 to 2011. Costs were measured according to Medicare payments converted from institutional billing records. Total and imaging costs were analyzed at 6, 12, 18, and 24 months after the end of treatment. Patient and provider demographic characteristics were also evaluated for potential associations with PET/CT use. RESULTS: Total costs in the PET/CT group were higher during the first 18 months after treatment (P = .002 at 6 months, P = .019 at 12 months, and P = .018 at 18 months) but was marginally significant (P = .05) at 24 months. In univariate analysis of demographic variables, patients who lived in a state different from the treatment center might have been more likely to receive PET/CT (odds ratio [OR], 1.76; P = .051). In multivariate analysis, patients treated in 2007 to 2010 (OR, 29.9; P < .001) or 2003 to 2006 (OR, 11.6; P = .002) were more likely to receive PET/CT than patients treated in 1999 to 2002. In addition, radiation oncologists with > 10 years of experience were more likely to use PET/CT than those with less experience, although this result might be confounded by the small number of providers. CONCLUSION: Use of PET/CT was associated with higher costs for 18 months after treatment, but the difference was at the borderline of statistical significance at 24 months.

The Texas Breast and Cervical Cancer Services (BCCS) program was established to address the socioeconomic disparities in stage at diagnosis and outcomes among breast cancer patients. This study examines the impact of Texas BCCS on stage at diagnosis among low socioeconomic status (SES) breast cancer patients. This is a retrospective analysis of women aged 40-64 years who were screened and diagnosed with breast cancer through the Texas BCCS program (participants) as compared with similar women living in low-SES census tracts and diagnosed outside the program (comparison group) during 1995-2008. Incident cases among the participants were compared with the comparison group as well. Stage at diagnosis was also analyzed separately for the years 1995-2002 and 2003-2008 in order to estimate the effect of BCCS-related Medicaid expansion in 2002. Over the study period of 1995-2008, BCCS participants had a 1.23 (P value

Objectives Given the uncertain cost of delivering community-based cancer screening programs, we developed a Markov simulation model to project the budget impact of implementing a comprehensive colorectal cancer (CRC) prevention program compared with the status quo. Methods The study modeled the impacts on the costs of clinical services, materials, and staff expenditures for recruitment, education, fecal immunochemical testing (FIT), colonoscopy, follow-up, navigation, and initial treatment. We used data from the Against Colorectal Cancer In Our Neighborhoods comprehensive CRC prevention program implemented in El Paso, Texas, since 2012. We projected the 3-year financial consequences of the presence and absence of the CRC prevention program for a hypothetical population cohort of 10,000 Hispanic medically underserved individuals. Results The intervention cohort experienced a 23.4% higher test completion rate for CRC prevention, 8 additional CRC diagnoses, and 84 adenomas. The incremental 3-year cost was $1.74 million compared with the status quo. The program cost per person was $261 compared with $86 for the status quo. The costs were sensitive to the proportion of high-risk participants and the frequency of colonoscopy screening and diagnostic procedures. Conclusions The budget impact mainly derived from colonoscopy-related costs incurred for the high-risk group. The effectiveness of FIT to detect CRC was critically dependent on follow-up after positive FIT. Community cancer prevention programs need reliable estimates of the cost of CRC screening promotion and the added budget impact of screening with colonoscopy.