A whole-slide foundation model for digital pathology from real-world data.

Digital pathology poses unique computational challenges, as a standard gigapixel slide may comprise tens of thousands of image tiles1-3. Prior models have often resorted to subsampling a small portion of tiles for each slide, thus missing the important slide-level context4. Here we present Prov-GigaPath, a whole-slide pathology foundation model pretrained on 1.3 billion 256 × 256 pathology image tiles in 171,189 whole slides from Providence, a large US health network comprising 28 cancer centres. The slides originated from more than 30,000 patients covering 31 major tissue types. To pretrain Prov-GigaPath, we propose GigaPath, a novel vision transformer architecture for pretraining gigapixel pathology slides. To scale GigaPath for slide-level learning with tens of thousands of image tiles, GigaPath adapts the newly developed LongNet5 method to digital pathology. To evaluate Prov-GigaPath, we construct a digital pathology benchmark comprising 9 cancer subtyping tasks and 17 pathomics tasks, using both Providence and TCGA data6. With large-scale pretraining and ultra-large-context modelling, Prov-GigaPath attains state-of-the-art performance on 25 out of 26 tasks, with significant improvement over the second-best method on 18 tasks. We further demonstrate the potential of Prov-GigaPath on vision-language pretraining for pathology7,8 by incorporating the pathology reports. In sum, Prov-GigaPath is an open-weight foundation model that achieves state-of-the-art performance on various digital pathology tasks, demonstrating the importance of real-world data and whole-slide modelling.

Cancer case trends following the onset of the COVID-19 pandemic: A community-based observational study with extended follow-up.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has impacted health care delivery worldwide. Cancer is a leading cause of death, and the impact of the pandemic on cancer diagnoses is an important public health concern. METHODS: This cross-sectional study retrospectively analyzed the electronic medical records of 80,138 cancer patients diagnosed between January 1, 2019, and May 31, 2021. Outcome measures included weekly number of new cancer cases and trends in weekly cancer cases, before and after the pandemic; patient demographics; and positive COVID-19 test rates. RESULTS: Beginning March 4, 2020, defined as the onset of the pandemic, weekly cancer cases declined precipitously (-110.0 cases per week [95% confidence interval, -190.2 to -29.8]) for 4 weeks, followed by a moderate recovery (+23.7 cases per week [9.1 to 38.4]) of 10 weeks duration. Thereafter, weekly cancer cases trended slowly back toward pre-COVID-19 baseline levels. Following the pandemic onset, there was a cumulative year-over-year decline in cancer cases overall of 7.3%, including a 20.2%, 14.3%, and 12.8% decline in nonmelanoma skin cancer, breast cancer, and prostate cancer, respectively. Changes in case volumes were accompanied by variations in patient characteristics, including region, age, gender, race, insurance coverage, and COVID-19 positive test rates (P < .01 for all). Among patients tested for COVID-19, 5.3% had a positive result. CONCLUSIONS: The data in this study demonstrate a substantial reduction in cancer diagnoses following the onset of COVID-19, which appear to reach expected pre-COVID norms 12 months later. The largest reduction was noted among cancers that are typically screen-detected or identified as part of a routine wellness examination.

Can high-volume teams of anesthesiologists and surgeons decrease perioperative costs for pancreatic surgery?

BACKGROUND: Pancreatic surgery outcomes are associated with surgeon and center experience. Anesthesiologists as potential value drivers for pancreatic surgery have not been explored. We sought to evaluate whether anesthesiologists impact perioperative costs for pancreatic surgery. METHODS: Within an integrated health care system, 796 pancreatic surgeries (526 PDs and 270 DPs) were performed from January 2014 to June 2017. Mean direct operative and anesthesia costs driven by anesthesiologists (operating room (OR) time, anesthesia billing and anesthesia procedures) were determined for each case. The volumes of pancreatic cases per anesthesiologist were calculated, and those above the 75th percentile for volume (4 cases) were considered high-volume. A multivariable analysis of OR/anesthesia costs was performed. RESULTS: Mean OR and anesthesia costs for PD were $7064 for low-volume anesthesiologists (LVA), higher than $5968 for high-volume anesthesiologists (HVA) (p < 0.001). By multivariable analysis, HVA were associated with decreased costs of $2278 (p < 0.001). Teams of HVA and high-volume surgeons (HVS) were also associated with decreased mean costs of $1790 (p = 0.04). CONCLUSION: These data suggest that anesthesiologists experienced in the management of complex pancreatic operations such as PDs may contribute to improved efficiencies in care by reducing perioperative costs.

Toward structuring real-world data: Deep learning for extracting oncology information from clinical text with patient-level supervision.

Most detailed patient information in real-world data (RWD) is only consistently available in free-text clinical documents. Manual curation is expensive and time consuming. Developing natural language processing (NLP) methods for structuring RWD is thus essential for scaling real-world evidence generation. We propose leveraging patient-level supervision from medical registries, which are often readily available and capture key patient information, for general RWD applications. We conduct an extensive study on 135,107 patients from the cancer registry of a large integrated delivery network (IDN) comprising healthcare systems in five western US states. Our deep-learning methods attain test area under the receiver operating characteristic curve (AUROC) values of 94%-99% for key tumor attributes and comparable performance on held-out data from separate health systems and states. Ablation results demonstrate the superiority of these advanced deep-learning methods. Error analysis shows that our NLP system sometimes even corrects errors in registrar labels.

Real-world burden of chemotherapy-induced myelosuppression in patients with small cell lung cancer: a retrospective analysis of electronic medical data from community cancer care providers.

AIMS: Chemotherapy-induced myelosuppression, which commonly exhibits as neutropenia, anemia, or thrombocytopenia, represents a substantial burden for patients with cancer that affects health-related quality of life and increases healthcare resource utilization (HCRU). We evaluated the burden of myelosuppression among chemotherapy-treated patients with small cell lung cancer (SCLC) using real-world data from community cancer care providers in the Western United States. MATERIALS AND METHODS: This was a retrospective, observational analysis of electronic medical records (EMRs) from Providence St. Joseph Health hospital-associated oncology clinics between January 2016 and December 2019. Patient demographics were assessed from the date of first SCLC diagnosis in adult patients with chemotherapy-induced grade ≥3 myelosuppression in first-line (1L) or second-line-and-beyond (2L+) treatment settings. Myelosuppressive adverse events (AEs), treatment patterns, and HCRU were assessed from the date of chemotherapy initiation (index date) until 12 months, date of the last visit, date of death, or study end, whichever occurred earliest. RESULTS: Of 347 eligible patients with SCLC who had received chemotherapy (mean age 66; 49% female), all had received at least 1L treatment, and 103 (29.7%) had a 2L + treatment recorded within the EMR during the study period. Of 338 evaluable patients with longitudinal laboratory data, 206 (60.9%) experienced grade ≥3 myelosuppressive AEs, most commonly neutropenia, anemia, and thrombocytopenia (44.9, 41.1, and 25.4 per 100 patients, respectively). Rates of granulocyte colony-stimulating factor use and red blood cell transfusions were 47.0 and 41.7 per 100 patients, respectively. There was a trend toward increasing the use of supportive care interventions and visits to inpatient and outpatient facilities in patients with myelosuppressive AEs in more than one cell lineage. CONCLUSIONS: Chemotherapy-induced myelosuppression places a substantial real-world burden on patients with SCLC in the community cancer care setting. Innovations to protect bone marrow from chemotherapy-induced damage have the potential to reduce this burden.

PLAIN LANGUAGE SUMMARYThis study looked at the medical records of people with a particular type of lung cancer known as small cell lung cancer. When treated with chemotherapy, people with this cancer may develop a condition called myelosuppression. This causes people to have fewer blood cells, which can lead to tiredness, or increase the risk of infection or bleeding. The study looked at what types of chemotherapy people with small cell lung cancer were given, what the side effects of myelosuppression were, how often the side effects were reported, and what treatments were given to manage these side effects. The study also looked at whether people with side effects from myelosuppression needed more visits to the doctor or hospital. Around 3 out of 5 people in the study experienced serious side effects resulting in reduced numbers of white blood cells (which fight infection), red blood cells (which carry oxygen), or platelets (which help the blood to clot), and many needed drugs or blood transfusions to treat these side effects. On average, people with side effects from myelosuppression had more visits to healthcare facilities than those people without these side effects. The findings suggest that myelosuppression places a large burden on people with small cell lung cancer who are treated with chemotherapy.

A Random Forest Genomic Classifier for Tumor Agnostic Prediction of Response to Anti-PD1 Immunotherapy.

Tumor mutational burden (TMB), a surrogate for tumor neoepitope burden, is used as a pan-tumor biomarker to identify patients who may benefit from anti-program cell death 1 (PD1) immunotherapy, but it is an imperfect biomarker. Multiple additional genomic characteristics are associated with anti-PD1 responses, but the combined predictive value of these features and the added informativeness of each respective feature remains unknown. We evaluated whether machine learning (ML) approaches using proposed determinants of anti-PD1 response derived from whole exome sequencing (WES) could improve prediction of anti-PD1 responders over TMB alone. Random forest classifiers were trained on publicly available anti-PD1 data (n = 104), and subsequently tested on an independent anti-PD1 cohort (n = 69). Both the training and test datasets included a range of cancer types such as non-small cell lung cancer (NSCLC), head and neck squamous cell carcinoma (HNSCC), melanoma, and smaller numbers of patients from other tumor types. Features used include summaries such as TMB and number of frameshift mutations, as well as more gene-level features such as counts of mutations associated with immune checkpoint response and resistance. Both ML algorithms demonstrated area under the receiver-operator curves (AUC) that exceeded TMB alone (AUC 0.63 "human-guided," 0.64 "cluster," and 0.58 TMB alone). Mutations within oncogenes disproportionately modulate anti-PD1 responses relative to their overall contribution to tumor neoepitope burden. The use of a ML algorithm evaluating multiple proposed genomic determinants of anti-PD1 responses modestly improves performance over TMB alone, highlighting the need to integrate other biomarkers to further improve model performance.

Regional Thoracic Surgery Quality Collaboration Formation: Providence Thoracic Surgery Initiative.

BACKGROUND: Surgery quality initiatives improve clinical outcomes in cardiac and general surgery. No mature thoracic surgery (TS) regional effort has been described. METHODS: An intramural grant funded the Thoracic Surgery Initiative (TSI). Professional organization, site-specific administrative and clinical databases were used to identify surgeons performing TS across a large Western health system. Participants were recruited through stakeholder surveys, personal contact, and meetings. Differences in practices and outcomes were identified. Fourteen centers performing TS in 5 states formed the TSI with a mission to define, implement, and monitor TS quality. RESULTS: A TS data system based on The Society of Thoracic Surgeons General Thoracic Surgery Database was implemented. Clinical data from 2015 and 2016 revealed significant differences in outcomes. Clinical data allow quality implementation, including identification and propagation of internal best practices and monitoring. TS practice standardization was agreed to using predefined TS best practice components that were incorporated into standardized TS care documents. Standardized care document completion by providers was intended to provoke desired TS care. The standardized care documents reside on the system-wide electronic health record. Literature and substantial surgeon experience were used to develop standardized TS care pathways for important or common clinical scenarios (pneumonectomy, primary spontaneous pneumothorax, etc). The TSI internet site serves as a harbor for standardization products. CONCLUSIONS: The TSI is evolving. Surgeon engagement remains high. The TSI enabled surgeons to lead, set the agenda, and remain in control of our destiny. Indeed, health care cannot appropriately evolve without such physician vision, engagement, and leadership.

What Are the Most Significant Cost and Value Drivers for Pancreatic Resection in an Integrated Healthcare System?

BACKGROUND: An initiative was established to improve value-based care for pancreatic surgery in a large nonprofit health system. Cost data were presented bimonthly to a hepatobiliary clinical performance group via videoconference. STUDY DESIGN: The direct costs were calculated for all patients undergoing distal pancreatectomy (DP) and pancreaticoduodenectomy (PD) between January 2014 and July 2017. Median length of stay, 30-day and 90-day mortality rates, readmission rate, and costs were stratified by surgeon volume using 2 published criteria: "volume pledge" criteria (≥5 PDs/year) and Leapfrog criteria (≥11 PDs/year). RESULTS: There were 270 DPs and 526 PDs performed in 14 hospitals spanning 4 states. Median PD costs were lower for high-volume surgeons (≥5 PDs/year), $21,026 vs $24,706 (p = 0.005). High-volume surgeons had a shorter length of stay (9 days vs 11 days; p < 0.001) for PD and DP (6 days vs 7 days; p = 0.001). Increased costs for low-volume surgeons included operative/anesthesia costs ($7,321 vs $6,325; p = 0.03), room and board ($5,828 vs $4,580; p = 0.01), and intensive care costs ($4,464 vs $3,113; p = 0.04). Operating time was increased for high-volume surgeons for DP and PD (p < 0.001). There was no difference in 30-day or 90-day mortality rates or readmissions for DP or PD when stratified by volume pledge criteria. There was no difference in total costs for DP or PD when stratified by Leapfrog criteria. CONCLUSIONS: There was a significant cost reduction for PD but not DP when the threshold of 5 PDs was used as a definition of high volume. The sharing of detailed financial data with HPB surgeons on a regular basis provides an opportunity to evaluate practice patterns and thereby reduce direct costs.

Mammography Screening in a Large Health System Following the U.S. Preventive Services Task Force Recommendations and the Affordable Care Act.

BACKGROUND: Practice recommendations for mammography screening were issued by the U.S. Preventive Services Task Force in 2009 and expansion of insurance coverage was provided under the Patient Protection and Affordable Care Act soon thereafter, yet the influence of these changes on screening practices in the United States is not known. METHODS: To determine changes in mammography screening and their associations with new practice recommendations and the Affordable Care Act, we examined patient-level data from 249,803 screening mammograms from January 1, 2008 through December 31, 2012 in a large community-based health system in the northwestern United States. Associations were determined by an intervention analysis of time-series data method. RESULTS: Among women screened, 64% were age 50-74 years; 84% self-identified as white race; 62% had commercial insurance; and 70% were seen in facilities located in metropolitan areas. Practice recommendations were associated with decreased screening volumes among women age <40 (-37.4 mammograms/month; -39.4% change; P<0.001), 40-49 (-106.0 mammograms/month; -11.2% change; P<0.001), and ≥75 (-54.7 mammograms/month; -10.0% change; P<0.001), but not women age 50-74. Implementation of the Affordable Care Act was associated with increased screening among women age 50-74 (+184.3 mammograms/month; +7.2% change; P=0.001), but not women <40 or ≥75; increases for age 40-49 were of borderline statistical significance (+56.9 mammograms/month; +6% change; P=0.06). Practice recommendations were also associated with decreased screening for women with commercial insurance, while the Affordable Care Act was associated with increased screening for women with Medicare, Medicaid, or other noncommercial sources of payment. CONCLUSIONS: Mammography screening volumes in a large community health system decreased among women age <50 and ≥75 in association with new U.S. Preventive Services Task Force practice recommendations, while insurance coverage changes under the Affordable Care Act were associated with increased screening volumes among women age 50-74.

Merkel cell carcinoma: what makes a difference?

BACKGROUND: Merkel cell carcinoma (MCC) is a cutaneous neuroendocrine tumor that may spread via lymphatics and can therefore be staged with sentinel lymph node biopsy (SLNB). MCC is radiosensitive and chemosensitive, although the role of adjuvant therapy is still unclear. We examined the impact of different treatments on the outcome of MCC. METHODS: We performed a retrospective review of state cancer registry data from California, Oregon, and Washington of patients diagnosed with primary skin MCC between 1988 and 2012 (n = 4,038). Data were analyzed using Cox regression and Kaplan-Meier methods to examine disease-specific survival. RESULTS: Patients with positive nodes or no documented nodal evaluation had worse survival compared with node-negative patients. No nodal evaluation had decreased survival compared with lymph node evaluation by SLNB. Completion lymph node dissection conferred improved survival in patients with a positive SLNB. In clinically node-negative patients who had a positive SLNB, radiation and chemotherapy did not affect survival. CONCLUSIONS: Lymph node evaluation is an important component to MCC treatment. The role of adjuvant radiation and chemotherapy needs further evaluation.

Rates and indications for surgical breast biopsies in a community-based health system.

BACKGROUND: High rates of surgical breast biopsies in community hospitals have been reported but may misrepresent actual practice. METHODS: Patient-level data from 5,757 women who underwent breast biopsies in a large integrated health system were evaluated to determine biopsy types, rates, indications, and diagnoses. RESULTS: Between 2008 and 2010, 6,047 breast biopsies were performed on 5,757 women. Surgical biopsy was the initial diagnostic procedure in 16% (n = 942) of women overall and in 6% (72 of 1,236) of women with newly diagnosed invasive breast cancer. Invasive breast cancer was diagnosed in 72 women (8%) undergoing surgical biopsy compared with 1,164 (24%) undergoing core needle biopsy (P < .001, age adjusted). Main indications for surgical biopsies included symptomatic abnormalities, technical challenges, and patient choice. CONCLUSIONS: Surgical biopsy was the initial diagnostic procedure in 16% of women with breast abnormalities, comparable with rates at academic centers. Rates could be improved by more careful consideration of indications.

Development of an electronic breast pathology database in a community health system.

BACKGROUND: Health care systems rely on electronic patient data, yet access to breast tissue pathology results continues to depend on interpreting dictated free-text reports. OBJECTIVE: The objective was to develop a method to electronically search and categorize pathologic diagnoses of patients' breast tissue specimens from dictated free-text pathology reports in a large health system for multiple users including clinicians. DESIGN: A database integrating existing patient-level administrative and clinical information for breast cancer screening and diagnostic services and a web-based application for comprehensive searching of pathology reports were developed by a health system team led by pathologists. The Breast Pathology Assessment Tool and Hierarchy for Diagnosis (BPATH-Dx) provided search terms and guided electronic transcription of diagnoses from text fields on breast pathology clinical reports to standardized categories. APPROACH: Breast pathology encounters in the pathology database were matched with administrative data for 7332 women with breast tissue specimens obtained from an initial procedure in the health system from January 1, 2008 to December 31, 2011. Sequential queries of the pathology text based on BPATH-Dx categorized biopsies according to their worst pathological diagnosis, as is standard practice. Diagnoses ranged from invasive breast cancer (23.3%), carcinoma in situ (7.8%), atypical lesions (6.39%), proliferative lesions without atypia (27.9%), and nonproliferative lesions (34.7%), and were further classified into subcategories. A random sample of 5% of reports that were manually reviewed indicated 97.5% agreement. CONCLUSIONS: Sequential queries of free-text pathology reports guided by a standardized assessment tool in conjunction with a web-based search application provide an efficient and reproducible approach to accessing nonmalignant breast pathology diagnoses. This method advances the use of pathology data and electronic health records to improve health care quality, patient care, outcomes, and research.

Actualizing Personalized Healthcare for Women through Connected Data Systems: Breast Cancer Screening and Diagnosis.

BACKGROUND: Healthcare organizations have invested in electronic patient data systems, yet use of health data to optimize personalized care has been limited. PRIMARY STUDY OBJECTIVE: To develop and pilot an integrated source of health system data related to breast healthcare. METHODS/DESIGN: This study is a quality improvement project. Patient-level data from multiple internal sources were identified, mapped to a common data model, linked, and validated to create a breast healthcare-specific data mart. Linkages were based on matching algorithms using patient identifiers to group data from the same patient. Data definitions, a data dictionary, and indicators for quality and benchmarking aligned with standardized measures. Clinical pathways were developed to outline the patient populations, data elements, decision points, and outcomes for specific conditions. SETTING: Electronic data sources in a community-based health system in the United States. PARTICIPANTS: Women receiving breast cancer screening, prevention, and diagnosis services. MAIN OUTCOME MEASURES: Distribution of mammography examinations and pathologic results of breast biopsies. RESULTS: From 2008 to 2011, 200768 screening and 50200 diagnostic mammograms were obtained; rates varied by age over time. Breast biopsies for 7332 women indicated 23.3% with invasive breast cancer, 6.7% with ductal carcinoma in situ, and 70.0% with nonmalignant diagnoses that would not have been further differentiated by administrative codes alone. LIMITATIONS: Evaluation of validity and efficiency and additional tracking of clinical outcomes are needed. CONCLUSIONS: The creation of a patient-centered data system by connecting and integrating disparate data sources within a large health system allows customized analyses of data and improves capacity for clinical decision making and personalized healthcare.

Trends in research time, fellowship training, and practice patterns among general surgery graduates.

SUMMARY: A comparison of research experience, fellowship training, and ultimate practice patterns of general surgery graduates at a university-based surgical residency program. Research experience correlated with pursuing fellowship training and predicted an eventual academic career. More recently, graduates have been able to obtain fellowships without a dedicated research year, perhaps reflecting shifting fellowship training opportunities. BACKGROUND: We hypothesized that the relationships among dedicated research experience during residency, fellowship training, and career choices is changing as research and fellowship opportunities evolve. METHODS: Comparison of research experience, fellowship training, and ultimate practice patterns of general surgery graduates for 2 decades (1990-1999, n = 82; 2000-2009, n = 98) at a university-based residency program. Main outcome measures were number of years and area of research, fellowship training, and practice setting. RESULTS: Compared by decade, graduates became increasingly fellowship-trained (51.2% vs 67.3%; p < 0.05) and pursuit of fellowship training increased for both research and nonresearch participating graduates. The number of residents completing more than 1 year of research doubled (9.8% vs 22.4%, p < 0.05). By decade, the percentage of female graduates increased significantly (22% vs 41%, p = 0.005), with more women participating in dedicated research (17% vs 51%, p < 0.001) and seeking fellowships. The number of graduates going into specialty practice and academic/clinical faculty positions increased over time. CONCLUSIONS: Surgical residents have completed more dedicated research years and became increasingly fellowship-trained over time. The proportion of female graduates has increased with similar increases in research time and fellowship training in this subgroup. In the earlier decade, dedicated research experiences during surgical residency correlated with pursuing fellowship training, and predicted an eventual academic career. More recently, graduates have obtained fellowships and academic positions without dedicated research time, perhaps reflecting shifting fellowship opportunities.

False-negative sentinel lymph node biopsy in head and neck melanoma.

OBJECTIVE: The results of sentinel lymph node biopsy (SLNB) can be useful for staging and deciding on adjuvant treatment for patients with head and neck melanoma. False-negative SLNB can result in treatment delay. This study aimed to evaluate the characteristics and outcome of patients with false-negative SLNB in cutaneous melanoma of the head and neck. STUDY DESIGN: Longitudinal cohort study using a prospective institutional tumor registry. SETTING: Academic health center. SUBJECTS AND METHODS: Data from 153 patients who underwent SLNB for melanoma of the head and neck were analyzed. False-negative biopsy was defined as recurrence of tumor in a previously identified negative nodal basin. Statistical analysis was performed on registry data. RESULTS: Positive sentinel lymph nodes were identified in 19 (12.4%) patients. False-negative SLNB was noted in 9 (5.9%) patients, with a false-negative SLNB rate of 32.1%. Using multivariate regression analysis, only examination of a single sentinel lymph node was a significant predictor of false-negative SLNB (P = .01). The mean treatment delay for the false-negative SLNB group was 470 days compared with 23 days in the positive SLNB group (P < .001). The 2-year overall survival of patients with false-negative SLNB was 75% compared with 84% and 98% in positive and negative SLNB groups, respectively (P = .02). CONCLUSIONS: False-negative SLNB is more likely to occur when a single sentinel lymph node is harvested. There is significant treatment delay in patients with false-negative SLNB. False-negative SLNB is associated with poor outcome in patients with melanoma of the head and neck.

Comparison of pulmonary nodule detection rates between preoperative CT imaging and intraoperative lung palpation.

BACKGROUND: Recent advances in computed tomographic (CT) imaging have improved the detection rate of pulmonary metastasis. The aim of this study was to test the hypothesis that the pulmonary nodule detection rate for preoperative CT imaging and intraoperative palpation are now equivalent. METHODS: A retrospective review of 108 pulmonary metastasectomies in 84 patients was performed. The number of nodules detected on preoperative CT imaging by radiologist report was compared with the number of malignant nodules identified on pathology. Secondary outcome measures were operative approach and primary malignancy. RESULTS: Sarcoma metastases were the most common indication for resection (n = 54 [50%]). Thirty-three percent of metastasectomies were performed using a thoracoscopic approach. When thoracotomy was used, significantly more nodules were palpated and resected than were identified on preoperative CT imaging (3.24 vs 2.12, P < .001). Significantly more of these nodules were confirmed malignant on final pathology (2.40 vs 1.60, P = .01). This difference was not seen for thoracoscopic resections. CONCLUSIONS: Although the sensitivity of CT imaging has improved, a significant number of malignant pulmonary nodules are detected intraoperatively that are not identified on preoperative imaging. Patients undergoing pulmonary metastasectomy require careful intraoperative palpation of lung parenchyma, and therefore open thoracotomy remains the standard of care.

Sentinel lymph node staging of cutaneous melanoma: predictors and outcomes.

BACKGROUND: The authors updated their experience with sentinel lymph node (SLN) biopsy of clinically node negative (N0) melanoma to clarify indications, predictive factors, and outcomes. METHODS: A review of patients from the authors' institution's prospective database (n = 397) was performed; survival statistics were obtained from the institutional tumor registry. RESULTS: The SLN-positive (SLN+) rate was 16% (47 of 282) for lesions >1 mm thick; only 2 of 105 T1 lesions were SLN+. Thickness >2 mm, upper extremity primary, and ulceration predicted SLN+ status. Most SLN+ patients underwent completion node dissection; 12% had additional positive nodes. The false-negative SLN biopsy rate was 4.0%; the majority involved lower extremity and head and neck primaries. The overall complication rate was 26%; all were minor and resolved within 6 months. Overall 5-year survival rates were 73% and 92% for SLN+ and SLN-negative patients, respectively. SLN status was the most significant predictor of survival. CONCLUSIONS: SLN status, the most important determinant of outcome for clinically N0 melanoma, correlated with T stage, ulceration, and site. Staging of T1 lesions had low yield. A minority of completion node dissections yielded additional positive nodes.