Area-Based Geocoding: An Approach to Exposure Assessment Incorporating Positional Uncertainty.

While the spatial resolution of exposure surfaces has greatly improved, our ability to locate people in space remains a limiting factor in accurate exposure assessment. In this case-control study, two approaches to geocoding participant locations were used to study the impact of geocoding uncertainty on the estimation of ambient pesticide exposure and breast cancer risk among women living in California's Central Valley. Residential and occupational histories were collected and geocoded using a traditional point-based method along with a novel area-based method. The standard approach to geocoding uses centroid points to represent all geocoded locations, and is unable to adapt exposure areas based on geocode quality, except through the exclusion of low-certainty locations. In contrast, area-based geocoding retains the complete area to which an address matched (the same area from which the centroid is returned), and therefore maintains the appropriate level of precision when it comes to assessing exposure by geography. Incorporating the total potential exposure area for each geocoded location resulted in different exposure classifications and resulting odds ratio estimates than estimates derived from the centroids of those same areas (using a traditional point-based geocoder). The direction and magnitude of these differences varied by pesticide, but in all cases odds ratios differed by at least 6% and up to 35%. These findings demonstrate the importance of geocoding in exposure estimation and suggest it is important to consider geocode certainty and quality throughout exposure assessment, rather than simply using the best available point geocodes.

A state-wide population-based evaluation of cervical cancers arising during opportunistic screening in the United States.

OBJECTIVE: Despite widespread cervical screening, an estimated 13,800 women will be diagnosed with cervical cancer in the United States in 2020. To inform improvements, the screening histories of women diagnosed with cervical cancer in New Mexico were assessed. METHODS: Data were collected on all cervical screening, diagnostic tests and treatment procedures for all women diagnosed with cervical cancer aged 25-64 yrs. in New Mexico from 2006 to 2016. Women were categorized by their screening attendance in the 5-40 months (screening interval) and 1-4 months (peri-diagnostic interval) prior to cancer diagnosis. RESULTS: Of the 504 women diagnosed between May 2009-December 2016, 64% were not screened or had only inadequate screening tests in the 5-40 months prior to diagnosis, and 90 of 182 screened women (49%) had only negative screens in this period. Only 32% (N = 162) of cervical cancers were screen-detected. Women with adenocarcinomas were more likely to have had a recent negative screen (41/57 = 722%) than women with squamous cancers (50/112 = 45%). Both older women (aged 45-64 years) and women with more advanced cancers were less likely to have been screened, and if screened, were more likely to have a false-negative outcome. Only 9% of cancers were diagnosed in women who did not attend biopsy or treatment after positive tests requiring clinical management. Screening currently prevents 35% of cancers, whereas full screening coverage could prevent 61% of cervical cancers. CONCLUSION: Improved screening coverage has the largest potential for reducing cervical cancer incidence, though there is also a role for improved recall procedures and screening sensitivity.

Impact of screening on cervical cancer incidence: A population-based case-control study in the United States.

Cervical cancer is widely preventable through screening, but little is known about the duration of protection offered by a negative screen in North America. A case-control study was conducted with records from population-based registries in New Mexico. Cases were women diagnosed with cervical cancer in 2006-2016, obtained from the Tumor Registry. Five controls per case from the New Mexico HPV Pap Registry were matched to cases by sex, age and place of residence. Dates and results of all cervical screening and diagnostic tests since 2006 were identified from the pap registry. We estimated the odds ratio of nonlocalized (Stage II+) and localized (Stage I) cervical cancer associated with attending screening in the 3 years prior to case-diagnosis compared to women not screened in 5 years. Of 876 cases, 527 were aged 25-64 years with ≥3 years of potential screening data. Only 38% of cases and 61% of controls attended screening in a 3-year period. Women screened in the 3 years prior to diagnosis had 83% lower risk of nonlocalized cancer (odds ratio [OR] = 0.17, 95% CI: 0.12-0.24) and 48% lower odds of localized cancer (OR = 0.52, 95% CI: 0.38-0.72), compared to women not screened in the 5 years prior to diagnosis. Women remained at low risk of nonlocalized cancer for 3.5-5 years after a negative screen compared to women with no negative screens in the 5 years prior to diagnosis. Routine cervical screening is effective at preventing localized and nonlocalized cervical cancers; 3 yearly screening prevents 83% of nonlocalized cancers, with no additional benefit of more frequent screening. Increasing screening coverage remains essential to further reduce cervical cancer incidence.

GIScience and cancer: State of the art and trends for cancer surveillance and epidemiology.

Maps are well recognized as an effective means of presenting and communicating health data, such as cancer incidence and mortality rates. These data can be linked to geographic features like counties or census tracts and their associated attributes for mapping and analysis. Such visualization and analysis provide insights regarding the geographic distribution of cancer and can be important for advancing effective cancer prevention and control programs. Applying a spatial approach allows users to identify location-based patterns and trends related to risk factors, health outcomes, and population health. Geographic information science (GIScience) is the discipline that applies Geographic Information Systems (GIS) and other spatial concepts and methods in research. This review explores the current state and evolution of GIScience in cancer research by addressing fundamental topics and issues regarding spatial data and analysis that need to be considered. GIScience, along with its health-specific application in the spatial epidemiology of cancer, incorporates multiple geographic perspectives pertaining to the individual, the health care infrastructure, and the environment. Challenges addressing these perspectives and the synergies among them can be explored through GIScience methods and associated technologies as integral parts of epidemiologic research, analysis efforts, and solutions. The authors suggest GIScience is a powerful tool for cancer research, bringing additional context to cancer data analysis and potentially informing decision-making and policy, ultimately aimed at reducing the burden of cancer.

Health Service Accessibility and Risk in Cervical Cancer Prevention: Comparing Rural Versus Nonrural Residence in New Mexico.

PURPOSE: Multiple intrapersonal and structural barriers, including geography, may prevent women from engaging in cervical cancer preventive care such as screening, diagnostic colposcopy, and excisional precancer treatment procedures. Geographic accessibility, stratified by rural and nonrural areas, to necessary services across the cervical cancer continuum of preventive care is largely unknown. METHODS: Health care facility data for New Mexico (2010-2012) was provided by the New Mexico Human Papillomavirus Pap Registry (NMHPVPR), the first population-based statewide cervical cancer screening registry in the United States. Travel distance and time between the population-weighted census tract centroid to the nearest facility providing screening, diagnostic, and excisional treatment services were examined using proximity analysis by rural and nonrural census tracts. Mann-Whitney test (P < .05) was used to determine if differences were significant and Cohen's r to measure effect. FINDINGS: Across all cervical cancer preventive health care services and years, women who resided in rural areas had a significantly greater geographic accessibility burden when compared to nonrural areas (4.4 km vs 2.5 km and 4.9 minutes vs 3.0 minutes for screening; 9.9 km vs 4.2 km and 10.4 minutes vs 4.9 minutes for colposcopy; and 14.8 km vs 6.6 km and 14.4 minutes vs 7.4 minutes for precancer treatment services, all P < .001). CONCLUSION: Improvements in cervical cancer prevention should address the potential benefits of providing the full spectrum of screening, diagnostic and precancer treatment services within individual facilities. Accessibility, assessments distinguishing rural and nonrural areas are essential when monitoring and recommending changes to service infrastructures (eg, mobile versus brick and mortar).

Use of attribute association error probability estimates to evaluate quality of medical record geocodes.

BACKGROUND: The utility of patient attributes associated with the spatiotemporal analysis of medical records lies not just in their values but also the strength of association between them. Estimating the extent to which a hierarchy of conditional probability exists between patient attribute associations such as patient identifying fields, patient and date of diagnosis, and patient and address at diagnosis is fundamental to estimating the strength of association between patient and geocode, and patient and enumeration area. We propose a hierarchy for the attribute associations within medical records that enable spatiotemporal relationships. We also present a set of metrics that store attribute association error probability (AAEP), to estimate error probability for all attribute associations upon which certainty in a patient geocode depends. METHODS: A series of experiments were undertaken to understand how error estimation could be operationalized within health data and what levels of AAEP in real data reveal themselves using these methods. Specifically, the goals of this evaluation were to (1) assess if the concept of our error assessment techniques could be implemented by a population-based cancer registry; (2) apply the techniques to real data from a large health data agency and characterize the observed levels of AAEP; and (3) demonstrate how detected AAEP might impact spatiotemporal health research. RESULTS: We present an evaluation of AAEP metrics generated for cancer cases in a North Carolina county. We show examples of how we estimated AAEP for selected attribute associations and circumstances. We demonstrate the distribution of AAEP in our case sample across attribute associations, and demonstrate ways in which disease registry specific operations influence the prevalence of AAEP estimates for specific attribute associations. CONCLUSIONS: The effort to detect and store estimates of AAEP is worthwhile because of the increase in confidence fostered by the attribute association level approach to the assessment of uncertainty in patient geocodes, relative to existing geocoding related uncertainty metrics.

The joint effects of census tract poverty and geographic access on late-stage breast cancer diagnosis in 10 US States.

This study evaluated independent and joint effects of census tract (CT) poverty and geographic access to mammography on stage at diagnosis for breast cancer. The study included 161,619 women 40+ years old diagnosed with breast cancer between 2004 -2006 in ten participating US states. Multilevel logistic regression was used to estimate the odds of late-stage breast cancer diagnosis for the entire study population and by state. Poverty was independently associated with late-stage in the overall population (poverty rates >20% OR=1.30, 95% CI=1.26- 1.35) and for 9 of the 10 states. Geographic access was not associated with late-stage diagnosis after adjusting for CT poverty. State-specific analysis provided little evidence that geographic access was associated with breast cancer stage at diagnosis, and after adjusting for poverty, geographic access mattered in only 1 state. Overall, compared to women with private insurance, the adjusted odds ratios for late stage at diagnosis among women with either no insurance, Medicaid, or Medicare were 1.80 (95% CI = 1.65, 1.96), 1.75 (95% CI = 1.68, 1.84), and 1.05 (95% CI 1.01, 1.08), respectively. Although geographic access to mammography was not a significant predictor of late-stage breast cancer diagnosis, women in high poverty areas or uninsured are at greatest risk of being diagnosed with late-stage breast cancer regardless of geographic location and may benefit from targeted interventions.

The effect of administrative boundaries and geocoding error on cancer rates in California.

Geocoding is often used to produce maps of disease rates from the diagnosis addresses of incident cases to assist with disease surveillance, prevention, and control. In this process, diagnosis addresses are converted into latitude/longitude pairs which are then aggregated to produce rates at varying geographic scales such as Census tracts, neighborhoods, cities, counties, and states. The specific techniques used within geocoding systems have an impact on where the output geocode is located and can therefore have an effect on the derivation of disease rates at different geographic aggregations. This paper investigates how county-level cancer rates are affected by the choice of interpolation method when case data are geocoded to the ZIP code level. Four commonly used areal unit interpolation techniques are applied and the output of each is used to compute crude county-level five-year incidence rates of all cancers in California. We found that the rates observed for 44 out of the 58 counties in California vary based on which interpolation method is used, with rates in some counties increasing by nearly 400% between interpolation methods.

Breast cancer stage at diagnosis: is travel time important?

Recent studies have produced inconsistent results in their examination of the potential association between proximity to healthcare or mammography facilities and breast cancer stage at diagnosis. Using a multistate dataset, we re-examine this issue by investigating whether travel time to a patient's diagnosing facility or nearest mammography facility impacts breast cancer stage at diagnosis. We studied 161,619 women 40 years and older diagnosed with invasive breast cancer from ten state population based cancer registries in the United States. For each woman, we calculated travel time to their diagnosing facility and nearest mammography facility. Logistic multilevel models of late versus early stage were fitted, and odds ratios were calculated for travel times, controlling for age, race/ethnicity, census tract poverty, rural/urban residence, health insurance, and state random effects. Seventy-six percent of women in the study lived less than 20 min from their diagnosing facility, and 93 percent lived less than 20 min from the nearest mammography facility. Late stage at diagnosis was not associated with increasing travel time to diagnosing facility or nearest mammography facility. Diagnosis age under 50, Hispanic and Non-Hispanic Black race/ethnicity, high census tract poverty, and no health insurance were all significantly associated with late stage at diagnosis. Travel time to diagnosing facility or nearest mammography facility was not a determinant of late stage of breast cancer at diagnosis, and better geographic proximity did not assure more favorable stage distributions. Other factors beyond geographic proximity that can affect access should be evaluated more closely, including facility capacity, insurance acceptance, public transportation, and travel costs.

Geographic proximity to treatment for early stage breast cancer and likelihood of mastectomy.

PURPOSE: Women with early stage breast cancer who live far from a radiation therapy facility may be more likely to opt for mastectomy over breast conserving surgery (BCS). The geographic dimensions of this relationship deserve further scrutiny. METHODS: For over 100,000 breast cancer patients in 10 states who received either mastectomy or BCS, a newly-developed software tool was used to calculate the shortest travel distance to the location of surgery and to the nearest radiation treatment center. The likelihood of receipt of mastectomy was modeled as a function of these distance measures and other demographic variables using multilevel logistic regression. RESULTS: Women traveling over 75 km for treatment are about 1.4 times more likely to receive a mastectomy than those traveling under 15 km. CONCLUSIONS: Geographic barriers to optimal breast cancer treatment remain a valid concern, though most women traveling long distances to receive mastectomies are doing so after bypassing local options.