Natural History and Characteristics of ERBB2-mutated Hormone Receptor-positive Metastatic Breast Cancer: A Multi-institutional Retrospective Case-control Study from AACR Project GENIE

PURPOSE

We wanted to determine the prognosis and the phenotypic characteristics of hormone receptor-positive advanced breast cancer tumors harboring an ERBB2 mutation in the absence of a HER2 amplification.

EXPERIMENTAL DESIGN

We retrospectively collected information from the American Association of Cancer Research-Genomics Evidence Neoplasia Information Exchange registry database from patients with hormone receptor-positive, HER2-negative, ERBB2-mutated advanced breast cancer. Phenotypic and co-mutational features, as well as response to treatment and outcome were compared with matched control cases ERBB2 wild type.

RESULTS

A total of 45 ERBB2-mutant cases were identified for 90 matched controls. The presence of an ERBB2 mutation was not associated with worse outcome determined by overall survival (OS) from first metastatic relapse. No significant differences were observed in phenotypic characteristics apart from higher lobular infiltrating subtype in the ERBB2-mutated group. ERBB2 mutation did not seem to have an impact in response to treatment or time-to-progression (TTP) to endocrine therapy compared with ERBB2 wild type. In the co-mutational analyses, CDH1 mutation was more frequent in the ERBB2-mutated group (FDR < 1). Although not significant, fewer co-occurring ESR1 mutations and more KRAS mutations were identified in the ERBB2-mutated group.

CONCLUSIONS

ERBB2-activating mutation was not associated with a worse OS from time of first metastatic relapse, or differences in TTP on treatment as compared with a series of matched controls. Although not significant, differences in coexisting mutations (CDH1, ESR1, and KRAS) were noted between the ERBB2-mutated and the control group.

A Scalable Quality Assurance Process for Curating Oncology Electronic Health Records: The Project GENIE Biopharma Collaborative Approach

The American Association for Cancer Research Project Genomics Evidence Neoplasia Information Exchange Biopharma Collaborative is a multi-institution effort to build a pan-cancer repository of genomic and clinical data curated from the electronic health record. For the research community to be confident that data extracted from electronic health record text are reliable, transparency of the approach used to ensure data quality is essential.

Transparent QA processes for GENIE BPC ensure that the data can be used to support advances in precision oncology OR @jessicalavs of @MSKBiostats & coauthors discuss @AACR Project GENIE BPC, a multi-institution effort to aggregate clinical plus genomic data for patients with cancer. Transparent QA processes for GENIE BPC ensure that the data can be used to support advances in precision oncology.

Implications of Selection Bias Due to Delayed Study Entry in Clinical Genomic Studies

Importance

Real-world data sets that combine clinical and genomic data may be subject to left truncation (when potential study participants are not included because they have already passed the milestone of interest at the time of study recruitment). The lapse between diagnosis and molecular testing can present analytic challenges and threaten the validity and interpretation of survival analyses.

Observations

Effects of ignoring left truncation when estimating overall survival are illustrated using data from the American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange Biopharma Collaborative (GENIE BPC), and a straightforward risk-set adjustment approach is described. Ignoring left truncation results in overestimation of overall survival: unadjusted median survival estimates from diagnosis among patients with stage IV non-small cell lung cancer or stage IV colorectal cancer were overestimated by more than 1 year.

Conclusions and Relevance

Clinicogenomic data are a valuable resource for evaluation of real-world cancer outcomes and should be analyzed using appropriate methods to maximize their potential. Analysts must become adept at application of appropriate statistical methods to ensure valid, meaningful, and generalizable research findings.

Clinical Inflection Point Detection on the Basis of EHR Data to Identify Clinical Trial-Ready Patients With Cancer

PURPOSE

To inform precision oncology, methods are needed to use electronic health records (EHRs) to identify patients with cancer who are experiencing clinical inflection points, consistent with worsening prognosis or a high propensity to change treatment, at specific time points. Such patients might benefit from real-time screening for clinical trials.

METHODS

Using serial unstructured imaging reports for patients with solid tumors or lymphoma participating in a single-institution precision medicine study, we trained a deep neural network natural language processing (NLP) model to dynamically predict patients' prognoses and propensity to start new palliative-intent systemic therapy within 30 days. Model performance was evaluated using Harrell's c-index (for prognosis) and the area under the receiver operating characteristic curve (AUC; for new treatment and new clinical trial enrollment). Associations between model outputs and manual annotations of cancer progression were also evaluated using the AUC.

RESULTS

A deep NLP model was trained and evaluated using 302,688 imaging reports for 16,780 patients. In a held-out test set of 34,770 reports for 1,952 additional patients, the model predicted survival with a c-index of 0.76 and initiation of new treatment with an AUC of 0.77. Model-generated prognostic scores were associated with annotation of cancer progression on the basis of manual EHR review (n = 1,488 reports for 110 patients with lung or colorectal cancer) with an AUC of 0.78, and predictions of new treatment were associated with annotation of cancer progression on the basis of manual EHR review with an AUC of 0.84.

CONCLUSION

Training a deep NLP model to identify clinical inflection points among patients with cancer is feasible. This approach could identify patients who may benefit from real-time targeted clinical trial screening interventions at health system scale.

Correlation Between Surrogate End Points and Overall Survival in a Multi-institutional Clinicogenomic Cohort of Patients With Non-Small Cell Lung or Colorectal Cancer

IMPORTANCE

Contemporary observational cancer research requires associating genomic biomarkers with reproducible end points; overall survival (OS) is a key end point, but interpretation can be challenging when multiple lines of therapy and prolonged survival are common. Progression-free survival (PFS), time to treatment discontinuation (TTD), and time to next treatment (TTNT) are alternative end points, but their utility as surrogates for OS in real-world clinicogenomic data sets has not been well characterized.

OBJECTIVE

To measure correlations between candidate surrogate end points and OS in a multi-institutional clinicogenomic data set.

DESIGN, SETTING, AND PARTICIPANTS

A retrospective cohort study was conducted of patients with non-small cell lung cancer (NSCLC) or colorectal cancer (CRC) whose tumors were genotyped at 4 academic centers from January 1, 2014, to December 31, 2017, and who initiated systemic therapy for advanced disease. Patients were followed up through August 31, 2020 (NSCLC), and October 31, 2020 (CRC). Statistical analyses were conducted on January 5, 2021.

EXPOSURES

Candidate surrogate end points included TTD; TTNT; PFS based on imaging reports only; PFS based on medical oncologist ascertainment only; PFS based on either imaging or medical oncologist ascertainment, whichever came first; and PFS defined by a requirement that both imaging and medical oncologist ascertainment have indicated progression.

MAIN OUTCOMES AND MEASURES

The primary outcome was the correlation between candidate surrogate end points and OS.

RESULTS

There were 1161 patients with NSCLC (648 women [55.8%]; mean [SD] age, 63 [11] years) and 1150 with CRC (647 men [56.3%]; mean [SD] age, 54 [12] years) identified for analysis. Progression-free survival based on both imaging and medical oncologist documentation was most correlated with OS (NSCLC: ρ = 0.76; 95% CI, 0.73-0.79; CRC: ρ = 0.73; 95% CI, 0.69-0.75). Time to treatment discontinuation was least associated with OS (NSCLC: ρ = 0.45; 95% CI, 0.40-0.50; CRC: ρ = 0.13; 95% CI, 0.06-0.19). Time to next treatment was modestly associated with OS (NSCLC: ρ = 0.60; 0.55-0.64; CRC: ρ = 0.39; 95% CI, 0.32-0.46).

CONCLUSIONS AND RELEVANCE

This cohort study suggests that PFS based on both a radiologist and a treating oncologist determining that a progression event has occurred was the surrogate end point most highly correlated with OS for analysis of observational clinicogenomic data.

Abstract 2620: Ignoring left truncation in overall survival within real-world genomic-phenomic data leads to inflated survival estimates

Studies linking genomic and phenomic data are subject to selection biases, including delayed entry or immortal time bias. Delayed entry can be problematic for time-to-event analyses, but utilization of appropriate statistical methods to account for delayed entry are underutilized. Delayed entry commonly occurs when genomic sequencing results are obtained after the start time for survival estimation.

To evaluate the impact of left truncation on overall survival (OS) estimates, we explored outcomes in patients with de novo stage IV non-small cell lung cancer (NSCLC) and colorectal cancer (CRC) from the AACR GENIE Biopharma Collaborative, who had genomic sequencing within a specified timeframe. We analyzed OS from diagnosis and from start of the most common first-line regimen, carboplatin/pemetrexed for NSCLC (N = 212 patients) and FOLFOX for CRC (N = 369 patients). We compared median OS using standard Kaplan-Meier methods to median OS using left truncation methods to account for delayed entry. All NSCLC and CRC patients underwent genomic sequencing after their diagnosis date. Among NSCLC patients on carboplatin/pemetrexed, 41% and among CRC patients on FOLFOX, 14% had sequencing determined after starting first-line regimen. The survfit function in R package survival was used, and the absolute differences and percent differences in median OS estimates were calculated.

Failure to account for delayed entry leads to an overestimation of OS, regardless of cohort and start date. Adjusting survival outcomes using left truncation methods reduces the influence of some aspects of selection bias and results in better estimates of time to event outcomes. Analyses from these cohorts can provide meaningful insights about survival outcomes outside the clinical trial setting and may support trial design and reliable selection of control arms. As such, it is imperative that analytic methods to account for the inflated survival estimates are incorporated.

EstimateCRC Stage IV (N = 658)NSCLC Stage IV (N = 722)Unadjusted Median (IQR) Overall Survival from Diagnosis (Years)3.2 (2.9, 3.4)2.3 (2.0, 2.5)Median (IQR) Overall Survival from Diagnosis in Years, Adjusting for Delayed Entry2.1 (1.9, 2.4)1.3 (1.1, 1.6)Difference in Medians (Years)1.11.0% Difference in Medians34%44%EstimateCRC Stage IV (N = 369)NSCLC Stage IV (N = 212)Unadjusted Median (IQR) Overall Survival from Most Common First-Line Regimen (Years)2.9 (2.6, 3.4)1.3 (1.0, 1.6)Median (IQR) Overall Survival from Most Common First-Line Regimen in Years, Adjusting for Delayed Entry2.1 (1.8, 2.5)0.9 (0.7, 1.2)Difference in Medians (Years)0.80.4% Difference in Medians28%31%

Citation Format: Samantha Brown, Jessica A. Lavery, Eva M. Lepisto, Caroline McCarthy, Hira Rizvi, Celeste Yu, Kenneth L. Kehl, Shawn M. Sweeney, Julia E. Rudolph, Nikolaus Schultz, Ritika Kundra, Brooke Mastrogiacomo, Phillipe Bedard, Jeremy L. Warner, Gregory J. Riely, Deborah Schrag, Katherine S. Panageas, The AACR Project GENIE Consortium. Ignoring left truncation in overall survival within real-world genomic-phenomic data leads to inflated survival estimates [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2620.

Pan-cancer evaluation of homologous repair deficiency somatic mutations and response to first-line anti-neoplastic therapy

10535

Background: Homologous recombination is a major mechanism of defective DNA repair, but it remains uncertain whether homologous repair deficient (HRD) tumors have favorable prognosis or are more/less likely to respond to treatment than tumors lacking such mutations. Objective: To determine whether lung (NSCLC) and colorectal (CRC) HRD+ tumors have better survival or response to chemotherapy than HRD- tumors. Methods: Patients with de novo stage IV NSCLC or CRC who had next generation sequencing (NGS) between 2015-2018 from one of four cancer centers were identified. Records were curated using the PRISSMM framework to ascertain treatment, overall survival (OS) and progression free survival based on imaging (PFS-I) and oncologists’ notes (PFS-M). Each NSCLC or CRC tumor was categorized as HRD+ if NGS revealed an oncogenic/likely oncogenic mutation in: ATM, BAP1, BARD1, BLM, BRCA1, BRCA2, BRIP1, CHEK2, FAM175A, FANCA, FANCC, NBN, PALB2, RAD50, RAD51, RAD51C, RTEL1, or MRE11A based on the OncoKB database. The tumor was categorized as HRD- if no oncogenic mutation in any of these genes was evident and HRD indeterminate (HRD?) if no mutation was identified but the panel did not include all genes. OS, PFS-I and PFS-M from start of first line therapy were reported by HRD status. The percentage with a good response to first line therapy (≥2x the median) and exceptional response (≥3x the median) was estimated for each endpoint. Results: For NSCLC 4% were HRD+, 59% HRD- and 37% HRD?. For CRC there were 5% HRD+, 60% HRD- and 35% HRD?. There were no significant differences for any survival endpoint between patients who were HRD+ vs HRD- in univariable analyses. The proportion of good and exceptional responders to first line systemic chemotherapy also did not vary by HRD status, though patients with HRD+ CRC were potentially more likely to be exceptional responders. Similarly, no differences between HRD+ and HRD- tumors were apparent for the subgroup receiving platinum containing therapy. Conclusions: NSCLC and CRC patients with somatic mutations in HRD oncogenic genes did not differ from patients lacking such a mutation with respect to OS or PFS. CRC patients with HRD+ tumors may be more likely to be exceptional responders, but sample sizes are limited. By May, the analysis will include breast and pancreatic cancer cases.[Table: see text]

Clinical and genomic predictors of brain metastases (BM) in non-small cell lung cancer (NSCLC): An AACR Project GENIE analysis

2032

Background: 30-50% of patients with non-early NSCLC will eventually develop BM, with a median survival of less than one year from BM diagnosis. There are no widely accepted clinical risk models for development of BM in patients without them at baseline. We predicted the binary risk of BM using clinical and genetic factors from a large multi-institutional cohort. Methods: Stage II-IV NSCLC patients from the AACR Project GENIE Biopharma Consortium dataset were eligible. This consisted of 4 academic institutions who curated clinical data of patients who had somatic next-generation tumor sequencing (NGS) between 2015-2017. We excluded patients who had BM at baseline, died within 30 days of NSCLC diagnosis, or did not undergo brain imaging. Covariates included demographics, anticancer therapies (received up to 90 days prior to BM development and within 5 years from NSCLC diagnosis), and NGS data; radiotherapy (RT) data were not available. NGS features included mutations and copy number alterations. These features were restricted to those classified as oncogenic by OncoKB. Univariate feature selection with Fisher’s test (p<.1) was performed on medication and genetic features. We compared 5 different machine learning models for prediction: random forest (RF), support vector machine (SVM), lasso regression, ridge regression, and an ensemble classifier. We split our data into training and test sets. 10-fold cross-validation was done on the training set for parameter tuning. The area under the receiver-operating curve (AUC) is reported on the test set. Results: 956 patients were included, 192 (20%) in the test set. Univariate features associated with BM were treatment with etoposide, Asian race, presence of bone metastases at NSCLC diagnosis, mutations in TP53 and EGFR, amplifications of ERBB2 and EGFR, and deletions of RB1, CDKN2A and CDKN2B. Univariate features inversely associated with BM were older age, treatment with nivolumab, vinorelbine, alectinib, pembrolizumab, atezolizumab, and gemcitabine, as well as mutations in NOTCH1 and KRAS. Ridge regression had the best AUC, 0.73 (Table). Conclusions: We achieved reasonable prediction performance using commonly obtained clinical and genomic information in non-early NSCLC. The biologic role of the associated alterations deserves further scrutiny; this study replicates similar findings for EGFR and KRAS in a much smaller cohort. Certain subsets of NSCLC patients may benefit from increased surveillance for BM and transition to drug therapies known to effectively cross the blood-brain barrier, e.g., nivolumab and alectinib. Inclusion of additional covariates, e.g., brain RT, may further improve model performance.[Table: see text]

Progression-free survival estimates in non-small cell lung cancer when RECIST is unavailable: Project GENIE’s integration of genomic, therapeutic and phenomic data

9622

Background: Molecular tumor profiling has become an integral component of oncology practice but linked genomic-phenomic data remain scarce. Recurrence, treatment response and progression are not structured consistently in medical records and this deficit has been a roadblock to discovery of biomarkers that are associated with favorable outcomes. Methods: The Genomics Evidence Neoplasia Information Exchange (GENIE) consortium is an AACR sponsored project to link and share genomic and phenomic data to promote discovery in precision medicine. 3 cancer centers that routinely perform somatic tumor profiling for advanced cancers agreed to curate anti-neoplastic treatment exposures and outcomes including recurrence, progression, response and survival using a standard method. 6 cancer types (lung, colorectal, breast, prostate, pancreas and bladder) were selected and a REDCAP database captures anti-neoplastic treatments, and specific elements from pathology, radiology and oncology reports. Curators abstract data using data fields that rely on the PRISSMM standard. “Real world” progression free survival (PFS) was identified based on curation of: 1) the text of radiologists’ reports for CT, PET/CT, PET and MRI scans (PFSI) and 2) medical oncologists’ notes (PFSM). PFSI and PFSM were estimated from the start of 1st line anti-neoplastic systemic therapy until progression or death for all patients with molecularly characterized non-small cell lung cancer (NSCLC). Results: Genomic sequencing was performed between 2015 and 2017 for 748 patients with NSCLC treated at three major cancer centers. Median age at diagnosis was 66 years (interquartile range 58, 73) and 43% were male. As shown in the table, when RECIST assessments are unavailable, estimates of PFS vary based on whether they are derived from radiologists’ or oncologists’ interpretations. Conclusions: Radiologists’ reports and oncologists’ reports provide different PFS estimates. Cohort studies should specify the method used to define “real world” endpoints. Project GENIE will have 1800 NSCLC patients with curated endpoints by the ASCO meeting. [Table: see text]

Patient-reported health literacy and numeracy among new patients seeking consultation at a comprehensive cancer center

7038

Background: Health literacy and numeracy are essential for patients to make informed cancer treatment decisions. Oncologists do not typically evaluate literacy and numeracy and vary in their ability to adapt health discussions to meet patients’ needs. Systematic ascertainment of literacy and numeracy may provide oncologists with useful information to help guide initial oncology consultations. Methods: We deploy an electronic new patient intake questionnaire (NPIQ) that includes health literacy and numeracy, basic demographics and cancer risk screening. Patients are considered to have limited health literacy and/or numeracy if they respond with either “somewhat”, “a little bit” or “not at all” to a single question: “How confident are you filling out medical forms?” or “How confident are you in understanding medical statistics?” respectively. Results: Between January 2018 and August 2019, 8418 (24.6%) of patients presenting for a new patient consultation responded to the NPIQ. Among respondents with non-missing data, limited health literacy was reported by 19.4% respondents with 13.9% reporting “not at all” and 33.1% reporting “not at all” or only “a little bit” of confidence completing medical forms. Limited health numeracy was reported by 33.2% respondents with 9.1% reporting “not at all”. Nearly 20% of respondents reported both limited health literacy and numeracy. Patients reporting lack of confidence completing medical forms or understanding medical statistics were older (20.3%, 30.7% ³ 70 years old), male (20.2%, 30.1%), and non-white (21.3%, 32.1%). Conclusions: A substantial proportion of cancer patients report lack of confidence in their ability to complete medical forms or understand medical statistics, potentially limiting the ability to actively engage in shared decision-making. Prospective identification of these social determinants of health prior to consultations may provide oncologists with information necessary to tailor health discussions and to provide materials that promote understanding and informed decision-making. [Table: see text]

Characteristics and Outcome of AKT1 E17K-Mutant Breast Cancer Defined through AACR Project GENIE, a Clinicogenomic Registry

AKT inhibitors have promising activity in AKT1 ^E17K-mutant estrogen receptor (ER)-positive metastatic breast cancer, but the natural history of this rare genomic subtype remains unknown. Utilizing AACR Project GENIE, an international clinicogenomic data-sharing consortium, we conducted a comparative analysis of clinical outcomes of patients with matched AKT1 ^E17K-mutant (n = 153) and AKT1-wild-type (n = 302) metastatic breast cancer. AKT1-mutant cases had similar adjusted overall survival (OS) compared with AKT1-wild-type controls (median OS, 24.1 vs. 29.9, respectively; P = 0.98). AKT1-mutant cases enjoyed longer durations on mTOR inhibitor therapy, an observation previously unrecognized in pivotal clinical trials due to the rarity of this alteration. Other baseline clinicopathologic features, as well as durations on other classes of therapy, were broadly similar. In summary, we demonstrate the feasibility of using a novel and publicly accessible clincogenomic registry to define outcomes in a rare genomically defined cancer subtype, an approach with broad applicability to precision oncology. SIGNIFICANCE: We delineate the natural history of a rare genomically distinct cancer, AKT1 ^E17K-mutant ER-positive breast cancer, using a publicly accessible registry of real-world patient data, thereby illustrating the potential to inform drug registration through synthetic control data.See related commentary by Castellanos and Baxi, p. 490.

Assessment of Deep Natural Language Processing in Ascertaining Oncologic Outcomes From Radiology Reports

Importance

A rapid learning health care system for oncology will require scalable methods for extracting clinical end points from electronic health records (EHRs). Outside of clinical trials, end points such as cancer progression and response are not routinely encoded into structured data.

Objective

To determine whether deep natural language processing can extract relevant cancer outcomes from radiologic reports, a ubiquitous but unstructured EHR data source.

Design, Setting, and Participants

A retrospective cohort study evaluated 1112 patients who underwent tumor genotyping for a diagnosis of lung cancer and participated in the Dana-Farber Cancer Institute PROFILE study from June 26, 2013, to July 2, 2018.

Exposures

Patients were divided into curation and reserve sets. Human abstractors applied a structured framework to radiologic reports for the curation set to ascertain the presence of cancer and changes in cancer status over time (ie, worsening/progressing vs improving/responding). Deep learning models were then trained to capture these outcomes from report text and subsequently evaluated in a 10% held-out test subset of curation patients. Cox proportional hazards regression models compared human and machine curations of disease-free survival, progression-free survival, and time to improvement/response in the curation set, and measured associations between report classification and overall survival in the curation and reserve sets.

Main Outcomes and Measures

The primary outcome was area under the receiver operating characteristic curve (AUC) for deep learning models; secondary outcomes were time to improvement/response, disease-free survival, progression-free survival, and overall survival.

Results

A total of 2406 patients were included (mean [SD] age, 66.5 [10.8] years; 1428 female [59.7%]; 2170 [90.2%] white). Radiologic reports (n = 14 230) were manually reviewed for 1112 patients in the curation set. In the test subset (n = 109), deep learning models identified the presence of cancer, improvement/response, and worsening/progression with accurate discrimination (AUC >0.90). Machine and human curation yielded similar measurements of disease-free survival (hazard ratio [HR] for machine vs human curation, 1.18; 95% CI, 0.71-1.95); progression-free survival (HR, 1.11; 95% CI, 0.71-1.71); and time to improvement/response (HR, 1.03; 95% CI, 0.65-1.64). Among 15 000 additional reports for 1294 reserve set patients, algorithm-detected cancer worsening/progression was associated with decreased overall survival (HR for mortality, 4.04; 95% CI, 2.78-5.85), and improvement/response was associated with increased overall survival (HR, 0.41; 95% CI, 0.22-0.77).

Conclusions and Relevance

Deep natural language processing appears to speed curation of relevant cancer outcomes and facilitate rapid learning from EHR data.

Time to adjuvant chemotherapy for breast cancer in National Comprehensive Cancer Network institutions

BACKGROUND

High-quality care must be not only appropriate but also timely. We assessed time to initiation of adjuvant chemotherapy for breast cancer as well as factors associated with delay to help identify targets for future efforts to reduce unnecessary delays.

METHODS

Using data from the National Comprehensive Cancer Network (NCCN) Outcomes Database, we assessed the time from pathological diagnosis to initiation of chemotherapy (TTC) among 6622 women with stage I to stage III breast cancer diagnosed from 2003 through 2009 and treated with adjuvant chemotherapy in nine NCCN centers. Multivariable models were constructed to examine factors associated with TTC. All statistical tests were two-sided.

RESULTS

Mean TTC was 12.0 weeks overall and increased over the study period. A number of factors were associated with a longer TTC. The largest effects were associated with therapeutic factors, including immediate postmastectomy reconstruction (2.7 weeks; P < .001), re-excision (2.1 weeks; P < .001), and use of the 21-gene reverse-transcription polymerase chain reaction assay (2.2 weeks; P < .001). In comparison with white women, a longer TTC was observed among black (1.5 weeks; P < .001) and Hispanic (0.8 weeks; P < .001) women. For black women, the observed disparity was greater among women who transferred their care to the NCCN center after diagnosis (P (interaction) = .008) and among women with Medicare vs commercial insurance (P (interaction) < .001).

CONCLUSIONS

Most observed variation in TTC was related to use of appropriate therapeutic interventions. This suggests the importance of targeted efforts to minimize potentially preventable causes of delay, including inefficient transfers in care or prolonged appointment wait times.

Documentation of pain in comprehensive cancer centers in the United States: a preliminary analysis

The National Comprehensive Cancer Network (NCCN), an organization of 19 of the world's leading cancer centers, developed and communicated a cancer pain treatment guideline. NCCN seeks to implement guidelines through performance measurement using a NCCN Oncology Outcomes Database. This is a preliminary report from the NCCN Cancer Pain Management Database Project. The primary objective of this NCCN Cancer Pain Management Database Project study is to evaluate the frequency, methods, and extent of documentation of cancer pain assessment and management at NCCN institutions. A pain data dictionary and related data collection forms were first developed. The records of 209 breast cancer patients with bone metastases were then studied. The frequency of pain mentions, type of pain assessment tool used, pain characteristics, type of clinician documenting pain, location in the medical record, and pain treatment characteristics were noted. The majority of clinical encounters included pain mentions, although considerable variability was found in pain documentation between providers and between inpatient and outpatient settings. Nurses more frequently recorded pain, usually as a numeric pain intensity score. Pain specialists were more likely to record a complete description of pain. A significant minority of patients experienced moderate to severe pain. In a small subgroup of patients with moderate to severe pain, pain treatment was not recorded. The undertreatment of cancer pain has been a focus of investigation and review for the past two decades. Quality improvement efforts to raise the standard of pain management have been underway. The results of this study highlight the need for standardization of pain documentation in comprehensive cancer centers as a prerequisite for the proper assessment of cancer pain and the improvement of clinical outcomes of pain management.

Reliability of staging, prognosis, and comorbidity data collection in the National Comprehensive Cancer Network (NCCN) non-Hodgkin lymphoma (NHL) multicenter outcomes database

BACKGROUND

Clinical trials and outcomes studies often rely on nonphysicians to abstract complex data from medical records, but the reliability of these data are rarely assessed.

METHODS

We used standardized charts of patients with non-Hodgkin lymphoma to assess the reliability of key clinical data elements abstracted by 6 clinical research associates (CRAs), 3 project staff, and 3 medical oncologists. We assessed reliability on 5 variables: MD-reported and rater-determined disease stage; International Prognostic Index (IPI; low-low intermediate, intermediate-high, high); Charlson comorbidity index score; and presence of any item from the Charlson index. Intraclass correlation coefficients (ICCs) of 0-0.20 were indicative of "slight", 0.21-0.40 indicated "fair", 0.41-0.60 indicated "moderate", 0.61-0.80 "substantial" and >0.80 "almost perfect" reliability.

RESULTS

By outcome, the ICC (95% confidence interval) values for MD-reported stage, rater-determined stage, and IPI were 0.86 (0.67, 0.94), 0.82 (0.59, 0.93), and 0.80 (0.55, 0.92), respectively. In contrast, the ICC (95% confidence interval) of the Charlson score, or presence of any Charlson comorbidity item was 0.47 (0.03, 0.75) and 0.61 (0.23, 0.83), respectively. Reliability varied by rater group; no rater group was consistently more reliable than others.

CONCLUSIONS

Trained CRAs abstracted key clinical variables with a very high degree of reliability, and performed at a level similar to study trainers and oncologists. Elements of the Charlson index were less reliable than other data types, possibly because of inherent ambiguity in the index itself.

Granulocyte-macrophage colony-stimulating factor and steel factor induce phosphorylation of both unique and overlapping signal transduction intermediates in a human factor-dependent hematopoietic cell line

Steel factor (SF), the ligand for the proto-oncogene c-kit, acts synergistically with GM-CSF or IL-3 to support the growth of normal human hematopoietic progenitor cells. We examined the effects of SF on GM-CSF or IL-3 induced proliferation of a human factor-dependent cell line, MO7. SF supported MO7 cell proliferation as well as IL-3 or GM-CSF alone, and its addition dramatically enhanced (three- to sixfold) maximal GM-CSF or IL-3 stimulated proliferation. SF did not increase the number or affinity of cell surface GM-CSF receptors. We examined several early events of signal transduction in an effort to elucidate the biochemical mechanisms of synergy of these factors. Since each of these three cytokines is believed to function in part through activation of a tyrosine kinase, we examined their effects on cellular phosphotyrosine containing proteins. Each cytokine induced rapid, transient, and concentration dependent tyrosine phosphorylation of a number of substrates. For GM-CSF and IL-3, these phosphoproteins were indistinguishable (150, 125, 106, 93, 80, 79, 73, 44, 42, and 36 kDa), while SF induced major or minor tyrosine phosphorylation of 205, 140-150, 116, 106, 94, 90, 80, 79, 73, 44, 42, 39, 36, 32 kDa phosphoproteins. Two other signal transduction intermediates known to be phosphorylated and activated by GM-CSF and IL-3, the 70-75 kDa Raf-1 kinase, and p42 mitogen-activated protein kinase-2 (MAPK), were also phosphorylated by SF. Combinations of GM-CSF or IL-3 with SF did not further increase the phosphorylation of Raf-1 or p42 MAPK when compared to any of the factors alone. In contrast SF, but not GM-CSF or IL-3, induced tyrosine phosphorylation of phospholipase C-gamma (PLC-gamma). These results indicate that SF and GM-CSF/IL-3 have partially overlapping effects on early signal transducing events, as well as striking differences, such as tyrosine phosphorylation of PLC-gamma. This cell line should provide a useful model system to investigate the complicated process of hematopoietic growth factor synergy.

Interferon-gamma increases the expression of the gene encoding the beta subunit of the granulocyte-macrophage colony-stimulating factor receptor

Granulocyte-macrophage colony-stimulating factor (GM-CSF) activates a broad range of myeloid cells through binding to high-affinity receptors (GM-CSF-R) consisting of at least two distinct subunits, GM-CSF-R alpha and GM-CSF-R beta. The genes of these GM-CSF-R subunits have been identified recently, but little is known about the regulation of their expression. In this study, we investigated the expression of the GM-CSF-R subunit genes in normal human monocytes. Out of a panel of various cytokines and factors tested, only interferon-gamma (IFN-gamma) affected the expression of one of the GM-CSF-R subunit genes by increasing the GM-CSF-R beta mRNA expression threefold to sixfold with no effect on GM-CSF-R alpha. Maximal effects occurred 2 to 4 hours after stimulation with 500 to 5,000 U/mL IFN-gamma. Nuclear run-on assays and mRNA half-life studies showed that IFN-gamma modestly enhanced the transcription of the GM-CSF-R beta gene and stabilized the GM-CSF-R beta mRNA, with the latter mechanism predominant. Pretreatment of the monocytes with cycloheximide did not abrogate the increase of GM-CSF-R beta mRNA expression induced by IFN-gamma, indicating that de novo protein synthesis was not required for this activity. When monocytes were exposed to IFN-gamma for 6 to 24 hours, the number of GM-CSF-R per cell was increased 79% as compared with controls, whereas the receptor affinity remained unchanged. These data indicate that the GM-CSF-R expression in monocytes may be upregulated by IFN-gamma via an increased expression of the beta subunit gene, involving both transcriptional and post-transcriptional mechanisms.

Human anti-murine antibody responses in ovarian cancer patients undergoing radioimmunotherapy with the murine monoclonal antibody OC-125

Human anti-murine antibody (HAMA) responses were monitored in 23 patients with recurrent or persistent epithelial ovarian carcinoma undergoing single-dose intraperitoneal radioimmunotherapy (RIT) with the murine monoclonal antibody OC-125. Sera of patients receiving escalating doses of OC-125 F(ab')2 (10-70 mg) radiolabeled with 18 to 141 mCi of iodine-131 were assayed for HAMA by a protein A-based radioimmunoassay. Overall, 70% of patients (16/23) developed HAMA within 10 to 46 days (median = 29) postinfusion, with peak values (23 +/- 6 to 325 +/- 10 micrograms/ml) at 32 to 102 days (median = 38). HAMA was undetectable prior to infusion in all cases and persisted up to 76 weeks. Of patients receiving a dose of 123 mCi or less, 80% (16/20) developed HAMA, whereas in the 140-mCi group, none of the three patients had detectable levels. Two patients in the 140-mCi group demonstrated dose-limiting bone marrow toxicity (severe thrombocytopenia and neutropenia). It is concluded that a single intraperitoneal dose of monoclonal antibody leads to a high incidence of HAMA production. The results also suggest that the likelihood of HAMA formation in patients who either had undergone recent chemotherapy or had received the highest dose of the radioimmunoconjugate is reduced. These observations may be of significance in designing multiple-dose therapy trials as HAMA has been demonstrated to decrease antibody-to-tumor binding and may potentially increase renal, hepatic, and hematologic toxicity associated with radioimmunotherapy.

Influence of human antimurine antibody on CA 125 levels in patients with ovarian cancer undergoing radioimmunotherapy or immunoscintigraphy with murine monoclonal antibody OC 125

Human antimurine antibody responses interfere with CA 125 antigen determinations by crosslinking the murine antiovarian carcinoma monoclonal antibody OC 125 with the second murine radiolabeled antibody used in the CA 125 radioimmunoassay. Serial CA 125 levels in 22 patients with epithelial ovarian carcinoma undergoing either radioimmunotherapy or radioimmunoscintigraphy with iodine 131-labeled F(ab')2 fragments of OC 125 were followed up for up to 96 weeks after infusion. Fourteen radioimmunoscintigraphy patients received 131I-labeled monoclonal antibody by the intraperitoneal (n = 5) or intravenous (n = 9) route: 10 of 14 had sera drawn at appropriate time points for human antimurine antibody detection; 8 of 10 had 1.3- to 363-fold increases in CA 125; 4 of 8 had detectable human antimurine antibody (18.5 to 22 and 575 to 36 micrograms/ml). Eight radioimmunotherapy patients received 131I-labeled monoclonal antibody by the intraperitoneal route: 8 of 8 displayed an apparent 4.8- to 3725-fold increase in CA 125 levels within 7 to 42 days after monoclonal antibody infusion; 6 of 8 had detectable human antimurine antibody (13 to 4 and 319 to 31 micrograms/ml). Adsorption of immunoglobulin G resulted in a 21% to 98% reduction in CA 125 antigen levels in 4 of 4 patients tested. In patients with demonstrable human antimurine antibody, CA 125 antigen levels obtained by the clinical CA 125 radioimmunoassay are spuriously elevated.