Developing a Conceptual Framework: Integrating Tumour, Macroenvironment and Resource (TMR) as a Composite Determinant of Ovarian Cancer Outcome in Diverse Resource Settings

Background: Ovarian cancer (OC) poses an escalating global health burden, with marked disparities in incidence, mortality, and survivorship. Social, psychological, and structural determinants, including deprivation, stigma, and access to specialist care, may influence outcomes but are not well-represented in existing models of cancer care. We introduce the Tumour, Macroenvironment and Resource (TMR) framework, a novel conceptual model exploring interactions among tumour biology, social determinants, and healthcare resources in OC survivorship and care. Methods: Framework development occurred in three phases. First, a narrative review identified factors influencing OC outcomes across tumour, macroenvironmental, and healthcare resource domains. Second, multi-criteria decision analysis (MCDA) was used to structure these factors within a preliminary framework and assign indicative domain weightings. Third, two cross-sectional expert opinion surveys were conducted to refine and validate the concept of the framework. The final model was then evaluated in a retrospective pilot cohort to assess the feasibility of collecting predefined TMR variables from routinely available clinical data. Results: The review identified limited evidence addressing broader determinants of health beyond biological prognostic factors. Available studies suggested interactions between tumour characteristics, social determinants, and healthcare infrastructure that may influence outcomes. A preliminary model allocated 50% weighting to tumour factors and 50% to combined macroenvironmental and healthcare resource factors. Expert surveys (n = 20 and n = 44) achieved consensus and informed development of the final TMR framework. Application to a UK pilot cohort of patients with OC (n = 42) demonstrated the feasibility of collecting variables across all TMR domains and identified multiple adverse factors across tumour, macroenvironmental, and resource domains. Conclusions: The TMR framework provides an integrative, hypothesis-generating model for exploring disparities in OC survivorship and care. Further retrospective and prospective validation are required before clinical or prognostic applications can be considered.

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Journal
Cancers
Published
2026-10-13
DOI
https://doi.org/10.3390/cancers18203299
Primary Topic
Ovarian cancer diagnosis and treatment
Type
article
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0.00
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article

Developing a Conceptual Framework: Integrating Tumour, Macroenvironment and Resource (TMR) as a Composite Determinant of Ovarian Cancer Outcome in Diverse Resource Settings

Ally Memon, Asima Mukhopadhyay, Adam Ruddock, Mohamed Elsebaei et al.
Cancers
Ovarian cancer diagnosis and treatment
article

Developing a Conceptual Framework: Integrating Tumour, Macroenvironment and Resource (TMR) as a Composite Determinant of Ovarian Cancer Outcome in Diverse Resource Settings

Ally Memon, Asima Mukhopadhyay, Adam Ruddock, Mohamed Elsebaei, Daity Bhattacharjee, on behalf of the Tumour-Macroenvironment-Resource (TMR) Global Review Group
article en

Abstract

Background: Ovarian cancer (OC) poses an escalating global health burden, with marked disparities in incidence, mortality, and survivorship. Social, psychological, and structural determinants, including deprivation, stigma, and access to specialist care, may influence outcomes but are not well-represented in existing models of cancer care. We introduce the Tumour, Macroenvironment and Resource (TMR) framework, a novel conceptual model exploring interactions among tumour biology, social determinants, and healthcare resources in OC survivorship and care. Methods: Framework development occurred in three phases. First, a narrative review identified factors influencing OC outcomes across tumour, macroenvironmental, and healthcare resource domains. Second, multi-criteria decision analysis (MCDA) was used to structure these factors within a preliminary framework and assign indicative domain weightings. Third, two cross-sectional expert opinion surveys were conducted to refine and validate the concept of the framework. The final model was then evaluated in a retrospective pilot cohort to assess the feasibility of collecting predefined TMR variables from routinely available clinical data. Results: The review identified limited evidence addressing broader determinants of health beyond biological prognostic factors. Available studies suggested interactions between tumour characteristics, social determinants, and healthcare infrastructure that may influence outcomes. A preliminary model allocated 50% weighting to tumour factors and 50% to combined macroenvironmental and healthcare resource factors. Expert surveys (n = 20 and n = 44) achieved consensus and informed development of the final TMR framework. Application to a UK pilot cohort of patients with OC (n = 42) demonstrated the feasibility of collecting variables across all TMR domains and identified multiple adverse factors across tumour, macroenvironmental, and resource domains. Conclusions: The TMR framework provides an integrative, hypothesis-generating model for exploring disparities in OC survivorship and care. Further retrospective and prospective validation are required before clinical or prognostic applications can be considered.

CancersVol. 18(20)
Northumbria University (GB), Natural History Society of Northumbria (GB), Teesside University (GB)
Openalex Percentile: Top 11%
Ovarian cancer diagnosis and treatment
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