Oncologists' influence on receipt of adjuvant chemotherapy: does it matter whom you see for treatment of curable breast cancer?

Multiple imputation with missing data indicators

Multiple imputation is a well-established general technique for analyzing data with missing values. A convenient way to implement multiple imputation is sequential regression multiple imputation, also called chained equations multiple imputation. In this approach, we impute missing values using regression models for each variable, conditional on the other variables in the data. This approach, however, assumes that the missingness mechanism is missing at random, and it is not well-justified under not-at-random missingness without additional modification. In this paper, we describe how we can generalize the sequential regression multiple imputation imputation procedure to handle missingness not at random in the setting where missingness may depend on other variables that are also missing but not on the missing variable itself, conditioning on fully observed variables. We provide algebraic justification for several generalizations of standard sequential regression multiple imputation using Taylor series and other approximations of the target imputation distribution under missingness not at random. Resulting regression model approximations include indicators for missingness, interactions, or other functions of the missingness not at random missingness model and observed data. In a simulation study, we demonstrate that the proposed sequential regression multiple imputation modifications result in reduced bias in the final analysis compared to standard sequential regression multiple imputation, with an approximation strategy involving inclusion of an offset in the imputation model performing the best overall. The method is illustrated in a breast cancer study, where the goal is to estimate the prevalence of a specific genetic pathogenic variant.

Epidemiology of diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL) in the United States and Western Europe: population-level projections for 2020-2025

Diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL) treatments have been rapidly evolving for patients treated in later lines of therapy (LoT). Country-specific cancer registry data for the US and Western Europe (WE) were combined with physician survey results to project the incidence, prevalence, and number of DLBCL and FL patients eligible for and treated by LoT between 2020 and 2025. The total number of incidents and prevalent cases of DLBCL and FL is expected to increase between 2020 and 2025 in the US and WE. 56% and 53% of the third line plus (3L+) eligible DLBCL patients and 60% and 55% of eligible FL patients initiated treatment in the US and WE, respectively. Further research is warranted to understand the reasons behind the high proportion of treatment eligible patients who do not initiate treatment, and potential differences between countries, especially in the 3L + settings.

Estimate of multiple myeloma patients by line of therapy in the USA: population-level projections 2020-2025

Aim: To report the results of a patient epidemiology model for multiple myeloma (MM) treatment by line of therapy (LOT) in the USA. Materials & methods: Surveillance, Epidemiology and End Results registry data and physician surveys were combined to project the incidence, prevalence and the number of MM patients treated with systemic therapy by LOT between 2020 and 2025. Results: Projected complete MM prevalence in the USA in 2020 was 144,922, increasing to 162,339 in 2025. Corresponding unique MM patients by LOT in 2020 were: 53,176 (1st; minimum-maximum: 47,304-59,212), 19,407 (2nd; 15,935-23,273), 6,481 (3rd; 5143-8877), 1649 (4th; 1146-2667) and 426 (5th; 217-876). Conclusion: MM incidence and prevalence by LOT is projected to continue to increase in the USA between 2020 and 2025.

A population-based study of invitation to and participation in clinical trials among women with early-stage breast cancer

PURPOSE

Although many studies clearly demonstrate disparities in cancer clinical trial enrollment, there is a lack of consensus on potential causes. Furthermore, virtually nothing is known about associations between patients' decision-making style and their participation in clinical trials.

METHODS

Women with newly diagnosed, stage 0-II breast cancer reported to the Georgia and Los Angeles County Surveillance, Epidemiology, and End Results (SEER) registries in 2013-2014 were surveyed approximately seven months after diagnosis. We investigated two primary outcome variables: (1) invitation to participate in a clinical trial, (2) participation in a clinical trial. We evaluated bivariate associations using Chi-squared tests and used multivariable logistic regression models to investigate associations between patient variables, including decision-making style, and the primary outcomes.

RESULTS

2578 patients responded (71% response rate); 30% were > age 65, 18% were black, 18% were Latina, 29% had ≤ high school education. 10% of patients reported invitation to participate in a clinical trial; 5% reported participation in a clinical trial. After adjustment younger age, receipt of chemotherapy or radiation, disease stage, and a more rational (versus more intuitive) decision-making style were associated with a higher odds of invitation to participate. Being married was associated with a higher odds of participation; having an annual family income ≥ $40,000 was associated with a lower odds of participation.

CONCLUSIONS

10% of patients reported invitation to participate in a clinical trial, and half of these reported participation. Invitation to participate varied by age and decision-making style, and participation varied by marital status and income.

Physician attitudes about cost consciousness for breast cancer treatment: differences by cancer sub-specialty

PURPOSE

High costs of cancer care place considerable burden on patients and society. Despite increasing recognition that providers should play a role in reducing care costs, how physicians across cancer specialties differ in their cost-consciousness has not been reported. We examined cost-consciousness regarding breast cancer care among medical oncologists, surgeons, and radiation oncologists.

METHODS

We identified 514 cancer surgeons, 504 medical oncologists, and 251 radiation oncologists by patient report through the iCanCare study. iCanCare identified newly diagnosed women with breast cancer through the Surveillance, Epidemiology, and End Results (SEER) registries of Georgia and Los Angeles. We queried providers on three dimensions of cost-consciousness: (1) perceived importance of cost saving for society, patients, practice, and payers; (2) awareness of patient out-of-pocket expenses; and (3) discussion of financial burden.

RESULTS

We received responses from 376 surgeons (73%), 304 medical oncologists (60%), and 169 radiation oncologists (67%). Overall levels of cost-consciousness were moderate, with scores ranging from 2.5 to 3.0 out of 5. After adjusting for covariates, surgeons had the lowest scores on all three cost-consciousness measures; medical oncologists had the highest scores. Pairwise contrasts showed surgeons had significantly lower scores than medical oncologists for all three measures and significantly lower scores than radiation oncologists for two of the three cost-consciousness variables: importance of cost saving and discussion of financial burden.

CONCLUSIONS

How cost-consciousness impacts medical decision-making across specialty and how policy, structural, and behavioral interventions might sensitize providers regarding cost-related matters merit further examination.

Patient Experiences and Clinician Views on the Role of Radiation Therapy for Ductal Carcinoma In Situ

PURPOSE

To evaluate patient experiences with decisions regarding radiation therapy (RT) for ductal carcinoma in situ (DCIS), and to assess clinician views on the role of RT for DCIS with favorable features in the present era.

METHODS AND MATERIALS

A sample of women with newly diagnosed breast cancer from the population-based Georgia and Los Angeles County Surveillance, Epidemiology, and End Results (SEER) registries were sent surveys approximately 2 months after undergoing breast-conserving surgery (BCS), with a 70% response rate. The analytic sample was limited to 538 respondents with unilateral DCIS. We also surveyed 761 surgeons and radiation oncologists treating breast cancer in those regions, of whom, 539 responded (71%).

RESULTS

After BCS, 23% of patients omitted RT, with twice the rate of omission in Los Angeles County relative to Georgia (31% vs 16%; P < .001). The most common reasons for omitting RT were advice from a clinician that it was not needed (62%) and concern about side effects (24%). Cost and transportation were not reported as influential considerations. After covariate adjustment, low- and intermediate-grade disease (odds ratio [OR] 5.5, 95% confidence interval [CI] 2.5-12; and OR 3.2, 95% CI 1.7-6.1, respectively) and Los Angeles County SEER site (OR 4.3, 95% CI 2.3-8.2) were significantly associated with greater RT omission. Of the responding clinicians, 62% would discuss RT omission for a patient with DCIS with favorable features. Clinicians in Los Angeles County were more likely to discuss RT omission than were those in Georgia (67% vs 56%; P = .01). Approximately one third of clinicians would obtain the Oncotype DX DCIS score.

CONCLUSIONS

The heterogeneity in RT omission after BCS for DCIS continues to be substantial, with systematic differences in provider opinions across the 2 regions we studied. Enhanced precision of recurrence estimates, guidance from professional organizations, and better communication are needed to improve the consistency of treatment in this controversial area.

Influence of provider factors and race on uptake of breast cancer gene expression profiling

BACKGROUND

Gene expression profiling (GEP) has been rapidly adopted for early breast cancer and can aid in chemotherapy decision making. Study results regarding racial disparities in testing are conflicting, and may reflect different care settings. To the authors' knowledge, data regarding the influence of provider factors on testing are scarce.

METHODS

The authors used a statewide, multipayer, insurance claims database linked to cancer registry records to examine the impact of race and provider characteristics on GEP uptake in a cohort of patients newly diagnosed with breast cancer between 2005 and 2012. Incidence proportion models were used to examine the adjusted likelihood of testing. Models were stratified by lymph node status (N0 vs N1).

RESULTS

Among 11,958 eligible patients, 23% of black and 26% of non-Hispanic white patients received GEP. Among patients with N0 disease, black individuals were 16% less likely to receive testing after adjustment for clinical factors and the provider's specialty and volume of patients with breast cancer (95% confidence interval, 0.77-0.93). Adjustment for provider characteristics did not attenuate the effect of race on testing. Patients of middle-volume providers were more likely to be tested compared with those with either high-volume or low-volume providers, whereas patients seeing a medical oncologist were more likely to be tested compared with those whose only providers were from surgical specialties.

CONCLUSIONS

Provider volume and specialty were found to be significant predictors of GEP use, but did not explain racial disparities in testing. Further research concerning the key contributors to lagging test use among black women is needed to optimize the equitable use of GEPs and support personalized treatment decision making for all patients. Cancer 2018;124:1743-51. © 2018 American Cancer Society.