Development and Utility of the Observational Research in Oncology Toolbox: Cancer Medications Enquiry Database-Healthcare Common Procedure Coding System (HCPCS)

Physical activity and pain in people with and without cancer

BACKGROUND

Performing physical activity may provide analgesic benefit, although this effect is more established for noncancer pain rather than cancer pain. The relationship between physical activity and pain outcomes in adults with and without a history of cancer was examined.

METHODS

Totals of 51,439 adults without a cancer history and 10,651 adults with a cancer history from the Cancer Prevention Study II Nutrition Cohort were included. Exposures included self-reported moderate to vigorous physical activity (MVPA) as well as 2-year change in MVPA. Pain outcomes included pain intensity (primary outcome) and analgesic use (secondary outcome).

RESULTS

MVPA was inversely associated with pain intensity for adults with (odds ratio [OR], 0.84 [≥15 metabolic equivalent of task (MET) h/week vs. <7.5 MET h/week]; 95% confidence interval [CI], 0.76-0.93) and without (OR, 0.79; 95% CI, 0.75-0.82) a history of cancer. Compared to remaining inactive, participants who became sufficiently active (cancer: OR, 0.76; 95% CI, 0.68-0.86; no cancer: OR, 0.73; 95% CI, 0.69-0.77), became inactive (cancer: OR, 0.79; 95% CI, 0.71-0.88; no cancer: OR, 0.84; 95% CI, 0.80-0.89), or remained sufficiently active (cancer: OR, 0.66; 95% CI, 0.60-0.72; no cancer: OR, 0.62; 95% CI, 0.60-0.65) also reported less pain. Physical activity was not related to analgesic use.

CONCLUSIONS

The relationship between physical activity and pain intensity was not substantially different between people with and without a history of cancer. Cancer survivors who perform more activity, or who increase their activity, may experience less pain than cancer survivors who consistently perform less.

PLAIN LANGUAGE SUMMARY

People who have had cancer often experience ongoing pain. Being physically active may help reduce the intensity of the pain they experience.

Long-term multimorbidity trajectories in older adults: The role of cancer, demographics, and health behaviors

BACKGROUND

Multimorbidity is associated with premature mortality and excess health care costs. The burden of multimorbidity is highest among patients with cancer, yet trends and determinants of multimorbidity over time are poorly understood.

METHODS

Via Medicare claims linked to Cancer Prevention Study II data, group-based trajectory modeling was used to compare National Cancer Institute comorbidity index score trends for cancer survivors and older adults without a cancer history. Among cancer survivors, multinomial logistic regression analyses evaluated associations between demographics, health behaviors, and comorbidity trajectories.

RESULTS

In 82,754 participants (mean age, 71.6 years [SD, 5.1 years]; 56.9% female), cancer survivors (n = 11,265) were more likely than older adults without a cancer history to experience the riskiest comorbidity trajectories: (1) steady, high comorbidity scores (remain high; odds ratio [OR], 1.36; 95% CI, 1.29-1.45), and (2) high scores that increased over time (start high and increase; OR, 1.51; 95% CI, 1.38-1.65). Cancer survivors who were physically active postdiagnosis were less likely to fall into these two trajectories (OR, 0.73; 95% CI, 0.64-0.84, remain high; OR, 0.42; 95% CI, 0.33-0.53, start high and increase) compared to inactive survivors. Cancer survivors with obesity were more likely to have a trajectory that started high and increased (OR, 2.83; 95% CI, 2.32-3.45 vs. normal weight), although being physically active offset some obesity-related risk. Cancer survivors who smoked postdiagnosis were also six times more likely to have trajectories that started high and increased (OR, 6.86; 95% CI, 4.41-10.66 vs. never smokers).

CONCLUSIONS

Older cancer survivors are more likely to have multiple comorbidities accumulated at a faster pace than older adults without a history of cancer. Weight management, physical activity, and smoking avoidance postdiagnosis may attenuate that trend.

Categorization of a Universal Coding System to Distinguish Use of Durable Medical Equipment and Supplies in Pediatric Patients

Importance

Although durable medical equipment and supplies (DMES) are commonly used to optimize the health and function in pediatric patients, little is known about the prevalence of use and spending on DMES.

Objective

To categorize the Healthcare Common Procedure Coding System (HCPCS) for distinguishing DMES types, and to measure the prevalence and related spending of DMES in pediatric patients using Medicaid.

Design, Setting, and Participants

This study is a cross-sectional analysis of the 2018 Merative Medicaid Database and included 4 569 473 pediatric patients aged 0 to 21 years enrolled in Medicaid in 12 US states from January 1 to December 31, 2018. Data were analyzed from February 2019 to April 2023.

Exposure

DMES exposure was identified with the Centers for Medicare & Medicaid Services HCPCS codes. Three pediatricians categorized HCPCS DMES codes submitted by vendors for reimbursement of dispensed DMES into DMES types and end-organ systems; 15 expert reviewers refined the categorization (2576 DMES codes, 164 DMES types, 14 organ systems).

Main Outcomes and Measures

The main outcome was DMES prevalence & Medicaid spending. The χ2 test was used to compare DMES prevalence and Wilcoxon rank sum tests were used to compare per-member-per-year (PMPY) spending by complex chronic conditions (CCC).

Results

Of the 4 569 473 patients in the study cohort, 49.3% were female and 56.1% were aged 5 to 15 years. Patients used 133 of 164 (81.1%) DMES types. The DMES prevalence was 17.1% (95% CI, 17.0%-17.2%) ranging from 10.1% (95% CI, 10.0%-10.2%) in patients with no chronic condition to 60.9% (95% CI, 60.8%-61.0%) for patients with 2 or more CCCs. The PMPY DMES spending was $593, ranging from $349 for no chronic condition to $4253 for 2 or more CCCs. Lens (7.9%), vision frames (6.2%), and orthotics for orthopedic injury (0.8%) were the most common DME in patients with no chronic condition. Enteral tube / feeding supplies (19.8%), diapers (19.2%), lower extremity orthotics (12.3%), wheelchair (9.6%), oxygen (9.0%), and urinary catheter equipment (4.2%) were among the most common DMES in children with 2 or more CCCs.

Conclusions and Relevance

In this cross-sectional study, HCPCS distinguished a variety of DME types and use across pediatric populations. Further investigation should assess the utility of the HCPCS DMES categorization with efforts to optimize the quality and safety of DMES use.

Fracture Risk Among Older Cancer Survivors Compared With Older Adults Without a History of Cancer

Importance

The number of cancer survivors living in the US is projected to be 26.1 million by 2040. Cancer survivors may be at increased risk of bone fractures, but research is limited in several important ways.

Objective

To investigate the associations of cancer diagnoses, including time since diagnosis and stage at diagnosis, with risks of pelvic, radial, and vertebral fractures (separately and combined) among older cancer survivors and compared with fracture risk among older adults without a history of cancer. Secondarily, to examine differences in risk of fracture stratified by modifiable behaviors, treatment, and cancer type.

Design, Setting, and Participants

This longitudinal cohort study used data from 92 431 older adults in the US Cancer Prevention Study II Nutrition Cohort linked with 1999 to 2017 Medicare claims. Data were analyzed from July 15, 2021, to May 3, 2022.

Exposures

Cancer history, time since cancer diagnosis, and stage at cancer diagnosis.

Main Outcomes and Measures

Hazard ratios (HRs) and 95% CIs for the risk of pelvic, radial, vertebral, and total frailty-related fractures were estimated using multivariate Cox proportional hazards regression. Stratification was used for secondary aims.

Results

Among 92 431 participants (mean [SD] age, was 69.4 [6.0] years, 51 820 [56%] women, and 90 458 [97.9%] White], 12 943 participants experienced a frailty-related bone fracture. Compared with participants without a history of cancer, cancer survivors who were diagnosed 1 to less than 5 years earlier with advanced stage cancer had higher risk of fracture (HR, 2.12; 95% CI, 1.75-2.58). The higher fracture risk in cancer survivors with recent advanced stage diagnosis (vs no cancer) was driven largely by vertebral (HR, 2.46; 95% CI, 1.93-3.13) and pelvic (HR, 2.46; 95% CI, 1.84-3.29) fracture sites. Compared with cancer survivors who did not receive chemotherapy, survivors who received chemotherapy were more likely to have a fracture; this association was stronger within 5 years of diagnosis (HR, 1.31; 95% CI, 1.09-1.57) than 5 or more years after diagnosis (HR, 1.22; 95% CI, 0.99-1.51). Although the HR for risk of fracture was lower among physically active cancer survivors 5 or more years after diagnosis (HR, 0.76; 95% CI, 0.54-1.07), this result was not statistically significant, whereas current smoking was significantly associated with higher risk of fracture (HR, 2.27; 95% CI, 1.55-3.33).

Conclusions and Relevance

Findings from this cohort study suggest that older adults with a history of cancer may benefit from clinical guidance on prevention of frailty-related fractures. If study findings are replicated, fracture prevention programs for survivors might include referrals for physical activity with cancer exercise professionals and smoking cessation programs.

Risk and Outcome of Breakthrough COVID-19 Infections in Vaccinated Patients With Cancer: Real-World Evidence From the National COVID Cohort Collaborative

PURPOSE

To provide real-world evidence on risks and outcomes of breakthrough COVID-19 infections in vaccinated patients with cancer using the largest national cohort of COVID-19 cases and controls.

METHODS

We used the National COVID Cohort Collaborative (N3C) to identify breakthrough infections between December 1, 2020, and May 31, 2021. We included patients partially or fully vaccinated with mRNA COVID-19 vaccines with no prior SARS-CoV-2 infection record. Risks for breakthrough infection and severe outcomes were analyzed using logistic regression.

RESULTS

A total of 6,860 breakthrough cases were identified within the N3C-vaccinated population, among whom 1,460 (21.3%) were patients with cancer. Solid tumors and hematologic malignancies had significantly higher risks for breakthrough infection (odds ratios [ORs] = 1.12, 95% CI, 1.01 to 1.23 and 4.64, 95% CI, 3.98 to 5.38) and severe outcomes (ORs = 1.33, 95% CI, 1.09 to 1.62 and 1.45, 95% CI, 1.08 to 1.95) compared with noncancer patients, adjusting for age, sex, race/ethnicity, smoking status, vaccine type, and vaccination date. Compared with solid tumors, hematologic malignancies were at increased risk for breakthrough infections (adjusted OR ranged from 2.07 for lymphoma to 7.25 for lymphoid leukemia). Breakthrough risk was reduced after the second vaccine dose for all cancers (OR = 0.04; 95% CI, 0.04 to 0.05), and for Moderna's mRNA-1273 compared with Pfizer's BNT162b2 vaccine (OR = 0.66; 95% CI, 0.62 to 0.70), particularly in patients with multiple myeloma (OR = 0.35; 95% CI, 0.15 to 0.72). Medications with major immunosuppressive effects and bone marrow transplantation were strongly associated with breakthrough risk among the vaccinated population.

CONCLUSION

Real-world evidence shows that patients with cancer, especially hematologic malignancies, are at higher risk for developing breakthrough infections and severe outcomes. Patients with vaccination were at markedly decreased risk for breakthrough infections. Further work is needed to assess boosters and new SARS-CoV-2 variants.

Cancer Registry Data Linkage of Electronic Health Record Data From ASCO's CancerLinQ: Evaluation of Advantages, Limitations, and Lessons Learned

PURPOSE

To evaluate the completeness of information for research and quality assessment through a linkage between cancer registry data and electronic health record (EHR) data refined by ASCO's health technology platform CancerLinQ.

METHODS

A probabilistic data linkage between Iowa Cancer Registry (ICR) and an Iowa oncology clinic through CancerLinQ data was conducted for cases diagnosed between 2009 and 2018. Demographic, cancer, and treatment variables were compared between data sources for the same patients, all of whom were diagnosed with one primary cancer. Treatment data and compliance with quality measures were compared among those with breast or prostate cancer; SEER-Medicare data served as a comparison. Variables captured only in CancerLinQ data (smoking, pain, and height/weight) were evaluated for completeness.

RESULTS

There were 6,175 patients whose data were linked between ICR and CancerLinQ data sets. Of those, 4,291 (70%) were diagnosed with one primary cancer and were included in analyses. Demographic variables were comparable between data sets. Proportions of people receiving hormone therapy (30% v 26%, P < .0001) or immunotherapy (22% v 12%, P < .0001) were significantly higher in CancerLinQ data compared with ICR data. ICR data contained more complete TNM stage, human epidermal growth factor receptor 2 testing, and Gleason score information. Compliance with quality measures was generally highest in SEER-Medicare data followed by the combined ICR-CancerLinQ data. CancerLinQ data contained smoking, pain, and height/weight information within one month of diagnosis for 88%, 52%, and 76% of patients, respectively.

CONCLUSION

Linking CancerLinQ EHR data with cancer registry data led to more complete data for each source respectively, as registry data provides definitive diagnosis and more complete stage information and laboratory results, whereas EHR data provide more detailed treatment data and additional variables not captured by registries.

Utilization of the Cancer Medications Enquiry Database (CanMED)-National Drug Codes (NDC): Assessment of Systemic Breast Cancer Treatment Patterns

Cancer Medications Enquiry Database (CanMED) is comprised of two interactive, nomenclature-specific databases within the Observational Research in Oncology Toolbox: CanMED-Healthcare Common Procedure Coding System (HCPCS) and CanMED-National Drug Code (NDC), described through this study. CanMED includes medications with a) a US Food and Drug Administration-approved cancer treatment or treatment-related symptom management indication, b) inclusion in treatment guidelines, or c) an orphan drug designation. To demonstrate the joint utility of CanMED, medication codes associated with female breast cancer treatment were identified and utilization patterns were assessed within Surveillance Epidemiology and End Results-Medicare (SEER) data. CanMED-NDC (11_2018 v.1.2.4) includes 6860 NDC codes: chemotherapy (1870), immunotherapy (164), hormone therapy (3074), and ancillary therapy (1752). Treatment patterns among stage I-IIIA (20 701) and stage IIIB-IV (2381) breast cancer patients were accordant with guideline-recommended treatment by stage and molecular subtype. CanMED facilitates identification of medications from observational data (eg, claims and electronic health records), promoting more standardized and efficient treatment-related cancer research.

Estimating Chemotherapy Use Among Patients With a Prior Primary Cancer Diagnosis Using SEER-Medicare Data

Cancer treatment studies commonly exclude patients with prior primary cancers due to difficulties in ascertaining for which site treatment is intended. Surveillance, Epidemiology, and End Results-Medicare patients 65 years and older diagnosed with an index colon or rectal cancer (CRC) or female breast cancer (BC) between 2004 and 2013 were included. Chemotherapy, defined as "any chemotherapy" and more restrictively as "chemotherapy with confirmatory diagnoses," was ascertained based on claims data within 6 months of index cancer diagnosis by prior cancer history. Any chemotherapy use was slightly lower among patients with a prior cancer (CRC: no prior = 17.4%, prior = 16.1%; BC: no prior = 12.9%, prior = 12.0%). With confirmatory diagnoses required, estimates were lower, especially among patients with a prior cancer (CRC: no prior = 16.8%, prior = 13.6%; BC: no prior = 12.6%, prior = 11.0%). These findings suggest that patients with prior cancers can be included in studies of chemotherapy use; requiring confirmatory diagnoses can increase treatment assignment confidence.