Breaking the Silos: Integrated Care for Cancer and Chronic Conditions

Cortis, Lauren J.; Ward, Paul; Koczwara, Bogda

doi:10.1007/978-981-10-1844-2_10

Cited by 2 publications

(2 citation statements)

References 81 publications

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“… 36 Taking such an approach requires our health systems to evolve beyond the current siloed models of care, where diabetes management primarily occurs in primary care, and cancer diagnosis and treatment primarily in secondary care; this model is disjointed, and not fit for purpose. 37 …”

Section: Discussionmentioning

confidence: 99%

Equity of Cancer and Diabetes Co-Occurrence: A National Study With 44 Million Person-Years of Follow-Up

Gurney

Stanley

Teng

et al. 2023

JCO Global Oncology

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PURPOSE The co-occurrence of diabetes and cancer is becoming increasingly common, and this is likely to compound existing inequities in outcomes from both conditions within populations. METHODS In this study, we investigate the co-occurrence of cancer and diabetes by ethnic groups in New Zealand. National-level diabetes and cancer data on nearly five million individuals over 44 million person-years were used to describe the rate of cancer in a national prevalent cohort of peoples with diabetes versus those without diabetes, by ethnic group (Māori, Pacific, South Asian, Other Asian, and European peoples). RESULTS The rate of cancer was greater for those with diabetes regardless of ethnic group (age-adjusted rate ratios, Māori, 1.37; 95% CI, 1.33 to 1.42; Pacific, 1.35; 95% CI, 1.28 to 1.43; South Asian, 1.23; 95% CI, 1.12 to 1.36; Other Asian, 1.31; 95% CI, 1.21 to 1.43; European, 1.29; 95% CI, 1.27 to 1.31). Māori had the highest rate of diabetes and cancer co-occurrence. Rates of GI, endocrine, and obesity-related cancers comprised a bulk of the excess cancers occurring among Māori and Pacific peoples with diabetes. CONCLUSION Our observations reinforce the need for the primordial prevention of risk factors that are shared between diabetes and cancer. Also, the commonality of diabetes and cancer co-occurrence, particularly for Māori, reinforces the need for a multidisciplinary, joined-up approach to the detection and care of both conditions. Given the disproportionate burden of diabetes and those cancers that share risk factors with diabetes, action in these areas is likely to reduce ethnic inequities in outcomes from both conditions.

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Section: Discussionmentioning

confidence: 99%

Equity of Cancer and Diabetes Co-Occurrence: A National Study With 44 Million Person-Years of Follow-Up

Gurney

Stanley

Teng

et al. 2023

JCO Global Oncology

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“…Morbidity is more likely to result from complications caused by comorbid conditions than from the primary illness itself. 1 It can refer to a variety of chronic diseases that are highly interconnected and share risk factors. 2,3…”

Section: Introductionmentioning

confidence: 99%

Modeling comorbidity of chronic diseases using coupled hidden Markov model with bivariate discrete copula

Oflaz

Yozgatlıgil

Selcuk‐Kestel

2023

Stat Methods Med Res

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A range of chronic diseases have a significant influence on each other and share common risk factors. Comorbidity, which shows the existence of two or more diseases interacting or triggering each other, is an important measure for actuarial valuations. The main proposal of the study is to model parallel interacting processes describing two or more chronic diseases by a combination of hidden Markov theory and copula function. This study introduces a coupled hidden Markov model with the bivariate discrete copula function in the hidden process. To estimate the parameters of the model and deal with the numerical intractability of the log-likelihood, we use a variational expectation maximization algorithm. To perform the variational expectation maximization algorithm, a lower bound of the model’s log-likelihood is defined, and estimators of the parameters are computed in the M-part. A possible numerical underflow occurring in the computation of forward–backward probabilities is solved. The simulation study is conducted for two different levels of association to assess the performance of the proposed model, resulting in satisfactory findings. The proposed model was applied to hospital appointment data from a private hospital. The model defines the dependency structure of unobserved disease data and its dynamics. The application results demonstrate that the model is useful for investigating disease comorbidity when only population dynamics over time and no clinical data are available.

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Breaking the Silos: Integrated Care for Cancer and Chronic Conditions

Cited by 2 publications

References 81 publications

Equity of Cancer and Diabetes Co-Occurrence: A National Study With 44 Million Person-Years of Follow-Up

Equity of Cancer and Diabetes Co-Occurrence: A National Study With 44 Million Person-Years of Follow-Up

Modeling comorbidity of chronic diseases using coupled hidden Markov model with bivariate discrete copula

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