Estimating the change in life expectancy after a diagnosis of cancer among the Australian population

Loss in life expectancy in patients with stage II-III cutaneous melanoma in Sweden: A population-based cohort study

BACKGROUND

Survival in cutaneous melanoma (CM) is heterogeneous. Loss in life expectancy (LLE) measures impact of CM on remaining lifespan compared to general population.

OBJECTIVES

Investigating LLE in operated stage II-III CM patients.

METHODS

Data from 8061 patients (aged 40-80 years) with stage II-III CM in Sweden, diagnosed between 2005 and 2018, were analyzed (Swedish Melanoma Registry). A flexible parametric survival model estimated life expectancy and LLE.

RESULTS

Based on 2018 diagnoses, stage II and III CM patients lost 2209 and 1902 life years, respectively. LLE was higher in stage III: 5.2 versus 10.9 years (stage II vs III 60-year-old females). Younger patients had higher LLE: 10.7 versus 3.9 years (stage II CM in 40 vs 70-year-old males). In stage II, females had lower LLE than males; 50-year-old females and males stage II CM had LLE equal to 7.3 and 8.3 years, respectively. LLE increased with higher substages, stage IIB resembling IIIB and IIC resembling IIIC-D.

LIMITATIONS

Extrapolation was used to estimate LLE. Varying stage group sizes require caution.

CONCLUSIONS

Our results are both clinically relevant and easy-to-interpret measures of the impact of CM on survival, but the results also summarize the prognosis over the lifetime of a CM patient.

Increase in the Life Expectancy of Patients with Cancer in the United States

BACKGROUND

Cancer is becoming more of a chronic disease due to improvements in treatment and early detection for multiple cancer sites. To gain insight on increased life expectancy due to these improvements, we quantified trends in the loss in expectation of life (LEL) due to a cancer diagnosis for six cancer sites from 1975 through 2018.

METHODS

We focused on patients diagnosed with female breast cancer, chronic myeloid leukemia (CML), colon and rectum cancer, diffuse large B-cell lymphoma (DLBCL), lung cancer, or melanoma between 1975 and 2018 from nine Surveillance, Epidemiology, and End Results cancer registries. Life expectancies for patients with cancer ages 50+ were modeled using flexible parametric survival models. LEL was calculated as the difference between general population life expectancy and life expectancy for patients with cancer.

RESULTS

Over 2 million patients were diagnosed with one of the six cancers between 1975 and 2018. Large increases in life expectancy were observed between 1990 and 2010 for female breast, DLBCL, and CML. Patients with colon and rectum cancer and melanoma had more gradual improvements in life expectancy. Lung cancer LEL only began decreasing after 2005. Increases in life expectancy corresponded with decreases in LEL for patients with cancer.

CONCLUSIONS

The reported gains in life expectancy largely correspond to progress in the screening, management, and treatment of these six cancers since 1975.

IMPACT

LEL provides an important public health perspective on how improvements in treatment and early detection and their impacts on survival translate into changes in cancer patients' life expectancy.

Long-term patient-reported outcomes of immediate breast reconstruction after mastectomy for breast cancer: population-based cohort study

BACKGROUND

Breast reconstruction is offered to improve quality of life for women after mastectomy for breast cancer, but information regarding the long-term patient-reported outcomes of different reconstruction procedures is currently lacking. The Brighter study aimed to evaluate long-term patient-reported outcomes after immediate breast reconstruction (IBR) in a population-based cohort.

METHODS

Women who underwent mastectomy with IBR for breast cancer in England between 1 January 2008 and 31 March 2009 were identified from National Health Service Hospital Episode Statistics. Surviving women were invited to complete the BREAST-Q, EQ-5D-5L™, and ICECAP-A at least 12 years after the index procedure. Questionnaires were scored according to developers' instructions and compared by IBR type.

RESULTS

Some 1236 women underwent IBR; 343 (27.8 per cent) had 2-stage expander/implant, 630 (51.0 per cent) latissimus dorsi, and 263 (21.3 per cent) abdominal flap reconstructions, with a mean(s.d.) follow-up of 13.3(0.5) years. Women who underwent abdominal flap reconstruction reported higher scores in all BREAST-Q domains than those who had other procedures. These differences remained statistically significant and clinically meaningful after adjusting for age, ethnicity, geographical region, socioeconomic status, smoking, BMI, and complications. The greatest difference was seen in scores for satisfaction with breasts; women who had abdominal flap reconstructions reported scores that were 13.17 (95 per cent c.i. 9.48 to 16.87) points; P < 0.001) higher than those among women who had two-stage expander/implant procedures. Women who underwent latissimus dorsi reconstruction reported significantly more pain/discomfort on the EQ-5D-5L™, but no other differences between procedures were seen.

CONCLUSION

Long-term patient-reported outcomes are significantly better following abdominal flap reconstruction than other traditional procedure types. These findings should be shared with women considering IBR to help them make informed decisions about their surgical options.

Methodological Considerations for Describing Medication Changes in Relation to Clinical Events and Death: An Applied Example in Patients with Type 2 Diabetes and Cancer

INTRODUCTION

Certain clinical events reduce life expectancy and necessitate a reassessment of patient treatment.

OBJECTIVE

To describe medication changes in relation to a cancer diagnosis and the end of life and to highlight challenges and limitations with such descriptions.

METHODS

From a cohort with all Danish patients with type 2 diabetes, we matched patients with incident cancer during 2000-2021 (n = 41,745) with patients without cancer (n = 166,994) using propensity scores. We described their medication usage from cancer diagnosis until death.

RESULTS

The 1- and 5-year mortality were 51% and 86%, respectively, in the cancer group, and 13% and 59% in the non-cancer group. In relation to cancer diagnosis and death, the use of symptomatic medications (e.g., opioids, benzodiazepines) increased (10-60 incident medications per 100 patient-months), and the use of preventive medications (e.g., antihypertensives, statins) decreased (5-30% fewer users). The changes in relation to the diagnosis were driven by patients with short observed lengths of survival (< 2 years). In contrast, changes occurring within a year before death were less dependent on survival strata, and > 60% used preventive medications in their last months.

CONCLUSIONS

Medication changes in relation to a cancer diagnosis were frequent and correlated to the length of survival. The results showcase the challenges and limited clinical utility of anchoring analyses on events or death. While the former diluted the results by averaging changes across patients with vastly different clinical courses, the latter leveraged information unavailable to the treating clinicians. While medication changes were common near death, preventive medications were often used until death.

Reference adjusted loss in life expectancy for population-based cancer patient survival comparisons - with an application to colon cancer in Sweden

BACKGROUND

The loss in life expectancy, LLE, is defined as the difference in life expectancy between cancer patients and that of the general population. It is a useful measure for summarising the impact of a cancer diagnosis on an individual's life expectancy. However, it is less useful for making comparisons of cancer survival across groups or over time, since the LLE is influenced by both mortality due to cancer and other causes and the life expectancy in the general population.

METHODS

We present an approach for making LLE estimates comparable across groups and over time by using reference expected mortality rates with flexible parametric relative survival models. The approach is illustrated by estimating temporal trends in LLE of colon cancer patients in Sweden.

RESULTS

The life expectancy of Swedish colon cancer patients has improved, but the LLE has not decreased to the same extent since the life expectancy in the general population has also increased. When using a fixed population and other-cause mortality, i.e. a reference-adjusted approach, the LLE decreases over time. For example, using 2010 mortality rates as the reference, the LLE for females diagnosed at age 65 decreased from 11.3 if diagnosed in 1976 to 7.2 if diagnosed in 2010, and from 3.9 to 1.9 years for women 85 years old at diagnosis.

CONCLUSION

The reference-adjusted LLE is useful for making comparisons across calendar time, or groups, since differences in other cause mortality are removed.

IMPACT

The reference-adjusted approach enhances the use of LLE as a comparative measure.

Quantifying Differences in Remaining Life Expectancy after Cancer Diagnosis, Aboriginal and Torres Strait Islanders, and Other Australians, 2005-2016

BACKGROUND

This study quantified differences in remaining life expectancy (RLE) among Aboriginal and Torres Strait Islander and other Australian patients with cancer. We assessed how much of this disparity was due to differences in cancer and noncancer mortality and calculated the population gain in life years for Aboriginal and Torres Strait Islanders cancer diagnoses if the cancer survival disparities were removed.

METHODS

Flexible parametric relative survival models were used to estimate RLE by Aboriginal and Torres Strait Islander status for a population-based cohort of 709,239 persons (12,830 Aboriginal and Torres Strait Islanders), 2005 to 2016.

RESULTS

For all cancers combined, the average disparity in RLE was 8.0 years between Aboriginal and Torres Strait Islanders (12.0 years) and other Australians (20.0 years). The magnitude of this disparity varied by cancer type, being >10 years for cervical cancer versus <2 years for lung and pancreatic cancers. For all cancers combined, around 26% of this disparity was due to differences in cancer mortality and 74% due to noncancer mortality. Among 1,342 Aboriginal and Torres Strait Islanders diagnosed with cancer in 2015 an estimated 2,818 life years would be gained if cancer survival disparities were removed.

CONCLUSIONS

A cancer diagnosis exacerbates the existing disparities in RLE among Aboriginal and Torres Strait Islanders. Addressing them will require consideration of both cancer-related factors and those contributing to noncancer mortality.

IMPACT

Reported survival-based measures provided additional insights into the overall impact of cancer over a lifetime horizon among Aboriginal and Torres Strait Islander peoples.

Randomized Controlled Trial Study of the Impact of a Spiritual Intervention on Hope and Spiritual Well-Being of Persons with Cancer

OBJECTIVES

To determine the impact of spiritual intervention on hope and spiritual well-being of persons with cancer.

METHODS

Randomized controlled trial in which 74 patients with cancer referring to a chemotherapy ward of Shahid Rajaie Hospital in Yasuj city, Iran, were participated. The eligible patients were randomly assigned to either intervention or control group. Spiritual-based intervention was performed based on the protocol in four main fields namely; religious, existence, emotional and social over 5 sessions before chemotherapy. The participants in the control group had received usual cares. Data were collected using Snyder's Hope Scale and Ellison's Scale Spiritual Well-Being Scale on a week before and after intervention.

RESULTS

The total mean scores of the scales of hope and spiritual well-being in both groups did not present statistical differences in the pre-intervention assessment. In contrast, at the post assessment, significant differences (p<0.001) were found in the mean scores between the intervention and control groups on the hope scale (60.9 versus 39.8) and on the spiritual well-being scale (94.3 versus 71.6).

CONCLUSIONS

Spiritual intervention could promote hope and spiritual well-being of persons with cancer.

Temporal improvements noted in life expectancy of patients with colorectal cancer; a Dutch population-based study

OBJECTIVE

Specific survival estimates are needed for the increasing number of colorectal cancer (CRC) survivors. The aim of this population-based study was to determine conditional loss in expectation of life (LEL) due to CRC.

STUDY DESIGN AND SETTING

All surgically treated patients with CRC registered in the Netherlands Cancer Registry with stage I-III between 1990-2016, were included (N = 203,216). Estimates of conditional LEL were predicted using flexible parametric models and the total life years lost due to cancer were estimated.

RESULTS

LEL decreased with older age and patients with rectal cancer or higher disease stage had highest LEL. In 2010, LEL for sixty-year old male and female patients was 2 vs. 2, 4 vs. 4, and 7 vs. 8 years for colon cancer, and 2 vs. 2, 4 vs. 5 and 7 vs. 8 years for rectal cancer, respectively. Conditional LEL in patients with CRC decreased during follow-up. Patients with combined stage I-III colon and rectal cancer in 2010 lost an estimated 18,628 and 11,336 life years.

CONCLUSION

This study quantified the impact of CRC on patient's life expectancy, both on individual and population level and demonstrated temporal improvements in CRC survival. These results provide meaningful information that can be used during follow-up.

Impact of area-level socioeconomic status and accessibility to treatment on life expectancy after a cancer diagnosis in Queensland, Australia

AIMS

This study quantifies geographic inequities in loss of life expectancy (LOLE) by area-level socioeconomic status (SES) and accessibility to treatment.

METHODS

Analysis was conducted using a population-based cancer-registry cohort (n = 371,570) of Queensland (Australia) residents aged 50-89 years, diagnosed between 1997-2016. Flexible parametric survival models were used to estimate LOLE by area-level SES and accessibility for all invasive cancers and the five leading cancers. The gain in life years that could be achieved if all cancer patients experienced the same relative survival as those in the least disadvantaged-high accessibility category was estimated for the 2016 cohort.

RESULTS

For all invasive cancers, men living in the most disadvantaged areas lost 34 % of life expectancy due to their cancer diagnosis, while those from the least disadvantaged areas lost 25 %. The corresponding percentages for women were 33 % and 23 %. Accessibility had a lower impact on LOLE than SES, with patients from low accessibility areas losing 0-4 % more life expectancy than those from high accessibility areas. For cancer patients diagnosed in 2016 (n = 24,423), an estimated 101,387 life years will be lost. This would be reduced by 19 % if all patients experienced the same relative survival as those from the least disadvantaged-high accessibility areas.

CONCLUSION

The impact of a cancer diagnosis on remaining life expectancy varies by geographical area. Establishing reasons why area disadvantage impacts on life expectancy is crucial to inform subsequent interventions that could increase the life expectancy of cancer patients from more disadvantaged areas.

Estimating the Loss in Expectation of Life and Relative Survival Rate among Hemodialysis Patients in Iran

BACKGROUND

Information regarding the prognosis and burden of diseases can be used by policymakers to determine competing health priorities. We aimed to assess the Relative Survival Rate (RSR) and loss of expectation of life (LEL) to evaluate the prognosis and burden of diseases in Hemodialysis (HD) patients.

STUDY DESIGN

A retrospective cohort study.

METHODS

We recruited 648 HD patients referred to three referral centers in Kerman City, Iran, from 2008 to 2019. RSR, was defined as the ratio of the observed and the expected survival rates of general population for persons of the same age and sex as patients in the current study. LEL was determined as the difference between corresponding life expectancies (LE). The extended Cox proportional hazard model was used to identify variables associated with the outcome.

RESULTS

Variables associated with outcome were diabetic status and age. In the 5th year of the follow-up study, the overall RSR was 0.57. In general, for HD patients, the estimation of LE and LEL was 22.6 and 12.36 year, respectively.

CONCLUSION

HD patients, especially older patients, showed a very poor prognosis, with a large amount of lost life expectancy. Therefore, they need more care and attention from health authorities. It is suggested to estimate the cost of eliminating the risk factors causing kidney diseases.

Does minimum follow-up time post-diagnosis matter? An assessment of changing loss of life expectancy for people with cancer in Western Australia from 1982 to 2016

BACKGROUND

Cancer survival has improved in Western Australia (WA) over recent decades. Loss of life expectancy (LOLE) is a useful measure for assessing cancer survival at a population-level. Some previous studies estimating LOLE have required a minimum follow-up beyond diagnosis to reduce the impact of modelled extrapolation, while others have not. The first aim of this study was to assess the impact of minimum length of follow-up on LOLE estimates for people diagnosed in 2006 with female breast, colorectal, prostate, lung, cervical, combined oesophageal and stomach cancers, and melanoma. Based on these results, the second aim was to assess temporal changes in LOLE for these cancer types for diagnoses between 1982 and 2016.

METHODS

Person-level linked cancer registry and mortality data were used for invasive primary cancer diagnoses for WA residents aged 15-89 years. The analysis for aim one included cases diagnosed from 1982 to the end of 2006, followed to the end of 2006 (i.e. no minimum follow-up), 2011 (i.e. five years minimum follow-up, assuming survival) or 2016 (i.e. 10 years minimum follow-up). To achieve the second study aim, the diagnostic period was extended to the end of 2016. Life expectancy estimates were obtained after fitting flexible parametric relative survival models. Single-year age and sex-specific death rates were used as a reference to estimate LOLE and proportionate loss of life expectancy.

RESULTS

Temporal changes were not reported for prostate, cervical, oesophageal and stomach cancers or melanoma, due to differences in LOLE estimates by minimum follow-up time, or estimate imprecision. Marked reductions in LOLE were observed for female breast and colorectal cancer. There was minimal absolute reduction for lung cancer, where LOLE remained high.

CONCLUSION

This study considered the appropriateness of including recent cancer diagnoses when assessing temporal changes in LOLE, finding variation in estimates with differing minimum follow-up or high parameter uncertainty for most included cancer types. Temporal changes in LOLE in-turn reflected changes in the life expectancy of the general population, cancer detection and management. These factors must be considered when estimating and interpreting LOLE estimates.

Changes in life expectancy for cancer patients over time since diagnosis

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Research question: how cancer impacts on LE changes during patients’ entire life

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LE increased in patients surviving the first years and decreasing thereafter.

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Patients’ LE in the long-term approached but seldom reached the general population’s LE.

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This method describes when cancer survivors’ excess risk of death became negligible.

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Life expectancy indicator is easy to be understood and interpreted by patients.

The aims of this study were to provide life expectancy (LE) estimates of cancer patients at diagnosis and LE changes over time since diagnosis to describe the impact of cancer during patients' entire lives. Cancer patients' LE was calculated by standard period life table methodology using the relative survival of Italian patients diagnosed in population-based cancer registries in 1985–2011 with follow-up to 2013. Data were smoothed using a polynomial model and years of life lost (YLL) were calculated as the difference between patients' LE and that of the age- and sex-matched general population. The YLL at diagnosis was highest at the youngest age at diagnosis, steadily decreasing thereafter. For patients diagnosed at age 45 years, the YLL was above 20 for lung and ovarian cancers and below 6 for thyroid cancer in women and melanoma in men. LE progressively increased in patients surviving the first years, decreasing thereafter, to approach that of the general population. YLL in the long run mainly depends on attained age. Providing quantitative data is essential to better define clinical follow-up and plan health care resource allocation. These results help assess when the excess risk of death from tumour becomes negligible in cancer survivors.

Do the Number of Cigarettes Smokes per Day Contribute to the Incident of Malignant Cancer?

Background:

The incident of malignant cancer due to smoking habit becomes a public health problem especially in the developing countries. Active smokers neglect to stop smoking even though various studies proved that smoking increases the risk of cancer. While, previous studies have assessed the incident risk of cancer but have not performed the validity of the measurement. The aim of this study is to know the number of cigarettes that contribute to the incidence of malignant cancer.

Methods:

A study with retrospective cohort design has been conducted by using a set of public data of Indonesia Family Life Survey (IFLS) in 2007 and 2014. All active smokers (n= 748) who were in good health condition in 2007, were traced in 2014 and then being diagnosed with cancer with considering age, gender, healthy eating habit, and regular physical activity. Data has been analysed by using logistic regression by performing Adjusted Risk Ratio (ARR) and the result of validity measurement.

Results:

The incident of malignant cancer in 2014 were skin, liver, stomach and oral cavity. Smoking 21-30 per day in 2007 were significantly increased risk of having malignant cancer in 2014 at ARR: 6.88; SE: 6.13 with the accuracy were 93.8%. The risk and accuracy were higher if smoke >30 cigarettes per day (ARR: 7.523;SE: 7.019; accuracy 95.5%). This study also found that the risk of cancer was significantly increase with age (99% CI; ARR: 1.065; SE: 0.026).

Conclusions:

Cigarette smoking behaviour increased the risk any types incident of cancer. Total number >20 cigarettes smoked per day contributes to the incidence of malignant cancer.

Understanding the impact of socioeconomic differences in colorectal cancer survival: potential gain in life-years

BACKGROUND

Colorectal cancer prognosis varies substantially with socioeconomic status. We investigated differences in life expectancy between socioeconomic groups and estimated the potential gain in life-years if cancer-related survival differences could be eliminated.

METHODS

This population-based study included 470,000 individuals diagnosed with colon and rectal cancers between 1998 and 2013 in England. Using flexible parametric survival models, we obtained a range of life expectancy measures by deprivation status. The number of life-years that could be gained if differences in cancer-related survival between the least and most deprived groups were removed was also estimated.

RESULTS

We observed up to 10% points differences in 5-year relative survival between the least and most deprived. If these differences had been eliminated for colon and rectal cancers diagnosed in 2013 then almost 8231 and 7295 life-years would have been gained respectively. This results for instance in more than 1-year gain for each colon cancer male patient in the most deprived group on average. Cancer-related differences are more profound earlier on, as conditioning on 1-year survival the main reason for socioeconomic differences were factors other than cancer.

CONCLUSION

This study highlights the importance of policies to eliminate socioeconomic differences in cancer survival as in this way many life-years could be gained.

Summarizing and communicating on survival data according to the audience: a tutorial on different measures illustrated with population-based cancer registry data

Survival data analysis results are usually communicated through the overall survival probability. Alternative measures provide additional insights and may help in communicating the results to a wider audience. We describe these alternative measures in two data settings, the overall survival setting and the relative survival setting, the latter corresponding to the particular competing risk setting in which the cause of death is unavailable or unreliable. In the overall survival setting, we describe the overall survival probability, the conditional survival probability and the restricted mean survival time (restricted to a prespecified time window). In the relative survival setting, we describe the net survival probability, the conditional net survival probability, the restricted mean net survival time, the crude probability of death due to each cause and the number of life years lost due to each cause over a prespecified time window. These measures describe survival data either on a probability scale or on a timescale. The clinical or population health purpose of each measure is detailed, and their advantages and drawbacks are discussed. We then illustrate their use analyzing England population-based registry data of men 15-80 years old diagnosed with colon cancer in 2001-2003, aiming to describe the deprivation disparities in survival. We believe that both the provision of a detailed example of the interpretation of each measure and the software implementation will help in generalizing their use.

In patients with unprovoked VTE, does the addition of FDG PET/CT to a limited occult cancer screening strategy offer good value for money? A cost-effectiveness analysis from the publicly funded health care systems

INTRODUCTION

Unprovoked venous thromboembolism (VTE) may be the first manifestation of an undiagnosed cancer. We assessed the cost-effectiveness of ¹⁸F-Fluorodesoxyglucose Positron Emission/Computed Tomography (FDG PET/CT) plus limited screening and limited screening strategies in patients with unprovoked VTE from the perspectives of the Ontario (Canada) and French health care systems.

METHODS

We conducted a cost-effectiveness analysis based on a published randomized controlled trial of 394 patients aged 18 years or older who were diagnosed with unprovoked VTE. We obtained data with respect to efficacy and health care utilization from the published trial. The primary measure of effectiveness was the number of avoided cases of delayed cancer diagnosis and the secondary measure of effectiveness was the quality adjusted life year (QALY) at the end of the study in each group. We used generalized linear models to estimate incremental cost-effectiveness ratios (ICER) while controlling for patient demographic and clinical characteristics. Results were presented as the incremental cost to avoid one case of delayed cancer diagnosis and the incremental cost per QALY gained. The 95% confidence intervals (CIs) were estimated using bootstrap re-sampling procedures with 5000 iterations.

RESULTS

Compared to a limited screening strategy, the ICER of limited strategy plus FDG PET/CT scan was C$ 26,840.19 (95% CI: C$ 24,046.51; C$ 34,581.53) per one avoided case of delayed cancer diagnosis from the Ontario health system perspective and €16,370.45 (95% CI: € 9904.48; € 39,578.91) per one avoided case of delayed cancer diagnosis from the French health system perspective. The probabilities that addition of FDG PET/CT to limited screening is cost-effective rose with increasing willingness to pay values. Compared with the limited screening, the extensive screening was associated with C$ 3412.85 per QALY gained (95% CI: 1463.89; -13,935.88) from the Ontario health system perspective and €2162.83 per QALY gained (95% CI 958.78; -10,544.42) from the French health system perspective.

CONCLUSION

Addition of a FDG PET/CT for occult cancer diagnosis was associated with better health outcomes (fewer cases of delayed cancer diagnosis and greater QALYs) and a higher cost from the perspective of publicly funded health care systems; the cost-effectiveness results are however highly uncertain.

The current application of the Royston-Parmar model for prognostic modeling in health research: a scoping review

BACKGROUND

Prognostic models incorporating survival analysis predict the risk (i.e., probability) of experiencing a future event over a specific time period. In 2002, Royston and Parmar described a type of flexible parametric survival model called the Royston-Parmar model in Statistics in Medicine, a model which fits a restricted cubic spline to flexibly model the baseline log cumulative hazard on the proportional hazards scale. This feature permits absolute measures of effect (e.g., hazard rates) to be estimated at all time points, an important feature when using the model. The Royston-Parmar model can also incorporate time-dependent effects and be used on different scales (e.g., proportional odds, probit). These features make the Royston-Parmar model attractive for prediction, yet their current uptake for prognostic modeling is unknown. Thus, the objectives were to conduct a scoping review of how the Royston-Parmar model has been applied to prognostic models in health research, to raise awareness of the model, to identify gaps in current reporting, and to offer model building considerations and reporting suggestions for other researchers.

METHODS

Five electronic databases and gray literature indexed in web sources from 2001 to 2016 were searched to identify articles for inclusion in the scoping review. Two reviewers independently screened 1429 articles, and after applying exclusion criteria through a two-step screening process, data from 12 studies were abstracted.

RESULTS

Since 2001, only 12 studies were identified that used the Royston-Parmar model in some capacity for prognostic modeling, 10 of which used the model as the basis for their prognostic model. The restricted cubic spline varied across studies in the number of interior knots (range 1 to 6), and only three studies reported knot placement. Three studies provided details about the baseline function, with two studies using a figure and the third providing coefficients. However, no studies provided adequate information on their restricted cubic spline to permit others to validate or completely use the model.

CONCLUSIONS

Despite the advantages of the Royston-Parmar model for prognostic models, they are not widely used in health research. Better reporting of details about the restricted cubic spline is needed, so the prognostic model can be used and validated by others.

REGISTRATION

The protocol was registered with Open Science Framework (https://osf.io/r3232/).

Spatially Varying Coefficient Inequalities: Evaluating How the Impact of Patient Characteristics on Breast Cancer Survival Varies by Location

An increasing number of studies have identified spatial differences in breast cancer survival. However little is known about whether the structure and dynamics of this spatial inequality are consistent across a region. This study aims to evaluate the spatially varying nature of predictors of spatial inequality in relative survival for women diagnosed with breast cancer across Queensland, Australia. All Queensland women aged less than 90 years diagnosed with invasive breast cancer from 1997 to 2007 and followed up to the end of 2008 were extracted from linked Queensland Cancer Registry and BreastScreen Queensland data. Bayesian relative survival models were fitted using various model structures (a spatial regression model, a varying coefficient model and a finite mixture of regressions model) to evaluate the relative excess risk of breast cancer, with the use of Markov chain Monte Carlo computation. The spatially varying coefficient models revealed that some covariate effects may not be constant across the geographic regions of the study. The overall spatial patterns showed lower survival among women living in more remote areas, and higher survival among the urbanised south-east corner. Notwithstanding this, the spatial survival pattern for younger women contrasted with that for older women as well as single women. This complex spatial interplay may be indicative of different factors impacting on survival patterns for these women.