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Table 1 Characteristics of included studies (n = 19)

From: Geographic and sociodemographic access to systemic anticancer therapies for secondary breast cancer: a systematic review

Author (year)

Sample size/no. of SBC patients included (%)

Study design

Country

Study population

SACT

Data source

Primary exposure

Exposures/covariates

Outcome of interest

Statistical analysis

Accordino et al. (2017) [26]

4251/4521 (100)

Retrospective cohort

USA

Women > 66, confirmed stage IV diagnosis between January 2002–2011, who died by 31 December 2012

Chemotherapy

SEER-Medicare

Time from diagnosis to death, costs of care, location of death

Age, year of diagnosis, marital status, race, hospital location (urban/rural), geographic region, comorbidities, HR status, No. of consultations

Receipt of end-of-life (EoL) care which included receipt of IV chemotherapy within 14 days of death

Logistic regression model to determine association between clinical, demographic and prognostic factors and receipt of EoL care

Alves et al. (2022) [33]

296/2525 (12)

Analytical cross-sectional study

Brazil

Patients with a confirmed BC diagnosis and without treatment from January to December 2019

Receipt of no SACT treatment

Cancer Hospital Registers (CHR)

-

Age group, race education, marital status, smoking status, alcohol status, region, family history, referral source, tumour, stage at diagnosis

Lack of access to BC treatment

Multivariate regression for factors associated with lack of access to SACT. odds ratio (OR) values with a 95% confidence interval (CI 95%), and estimated p-values

Cole et al. (2019) [34]

65,380/601,680 (11)

Retrospective cohort

USA

Patients > 40 years with metastatic prostate, lung, colon and breast cancer, diagnosed from January 1, 2004, to December 31, 2015

Chemotherapy

NCDB

Minority serving hospital (top decile) (MSH)

Age, race, year of diagnosis, insurance status, education income, comorbidities

Receipt of specialist palliative care (SPC) which included non-curative systemic chemotherapy

Multilevel logistic regression model which estimated odds of palliative care, adjusted for year of diagnosis, sex, race/ethnicity, insurance, income, educational level and cancer type

Falchook et al. (2017) [35]

5855/28,731 (20)

Retrospective cohort

USA

Patients > 18 < 64 years at time of death, who died between 1 Jan 2007 and 31 Dec 2014, with metastatic lung, colorectal, breast, pancreatic or prostate cancer with a diagnosis code reflecting metastatic disease during the 12 months preceding death

Chemotherapy

HIRD

Not specified

Age, year of death, population density, geographical region

Receipt of end-of-life (EoL) care which included chemotherapy in the last 14 days of life

Modified Poisson regression models to estimate risk for each outcome, adjusted for age, sex, geographic region, rural/urban location, year of death and regional education and income measures

Ferreira et al. (2020) [36]

10,816/151,931 (7)

Cross sectional

Brazil

Women > 18 > 70 diagnosed with breast cancer between 1998 and 2012

Unspecified SACT

NCI HRC

Not specified

Referral route, stage, insurance status, family history, time between diagnosis and treatment, geographic region, marital status, education, race, age

Time between diagnosis and commencement of treatment < 60 days or > 60 days

Logistic regression of time between diagnosis and treatment adjusted for clinical and epidemiologic characteristics. Addition and removal of variables in the model with significance levels for the removal and addition of variables in the models were p ≤ 0.20 and p > 0.05, respectively

Giap et al. (2023) [27]

60,685/60,685 (100%)

Retrospective cohort

USA

Patients aged > 18 years diagnosed with de novo stage IV breast cancer between 2010 and 2017

Chemotherapy (non-curative)

NCDB

Race and ethnicity

Facility type, income, insurance, education, residential setting, diagnosis age, comorbidities, diagnosis year, tumour grade, metastasis location, tumour receptor types, prior treatment(s)

Receipt of palliative care which included non-curative systemic therapy

Multivariable logistic regression analysis to identify variables associated with receipt of palliative care

Ozmen et al. (2015) [37]

29/1031 (3)

Questionnaire survey

Turkey

Women aged ≥ 18 years diagnosed with breast cancer within 6 months prior to questionnaire completion and undergoing/preparing for treatment

Unspecified SACT

Validated questionnaire

Not specified

Patient characteristics, symptom detection, first admission public/private hospital, surgical treatment, stage, lymph node involvement

Time to receipt of treatment defined as follows: (i) patient delay time (PDT), (ii) system delay time (SDT), and (iii) total delay time = sum of PDT and SDT

Chi-square tests and one-way analysis of variance (ANOVA) for group differences, principal components analysis for variable reduction and multiple regression analysis to build predictive models of PDT, SDT and TDT

Recondo et al. (2019) [38]

268/13 (5)

Retrospective cohort

Argentina

Patients ≥ 18 years old with diagnosis of non-small cell lung cancer (NSCLC) or breast cancer, stages I to IV treated with chemotherapy from January 1, 2016

Chemotherapy

Participant medical records

Not specified

Nationality, civil status, income, employment, transportation, travel time, stage, detection, performance status, treatment modality, chemotherapy provider

Time elapsed between diagnosis and receipt of treatment with chemotherapy

Kaplan–Meier curves were used to estimate patterns in time to diagnosis and to initial treatment and compared by the log rank test. Cox proportional hazard to explore association between health system and individual and sociodemographic and clinical variables

Sathe et al. (2023) [28]

6802/6802 (100%)

Retrospective cohort

USA

Patients ≥ 18 years old, diagnosed with HR-positive, HER2-negative MBC between February 3, 2015 (first FDA approval of a CDK4/6i) and July 31, 2021

Cyclin-dependent kinase 4 and 6 (CDK4 and CDK6) inhibitors

Flatiron health database (FHD)

Race

Age at MBC diagnosis, insurance coverage, site of treatment, performance status, year of metastatic diagnosis, the presence or absence of baseline leukopenia

Receipt of cyclin-dependent kinase 4 and 6 (CDK4 and CDK6) inhibitors palbociclib, ribociclib or abemaciclib documented in the FHD at any time after a MBC diagnosis

Multivariable logistic regression models were developed to analyse the association between CDK4/6i use and sociodemographic, clinical characteristics

Shih et al. (2009) [39]

42,804/207,581 (21)

Retrospective cohort

USA

Patients ≥ 18 years old newly diagnosed with metastatic breast cancer, colorectal cancer and NHL, who received immunotherapy treatment between 1998 and 2004

Immunotherapy

NCDB

Not specified

Age, race, ethnicity, year of diagnosis, insurance status, income, education, facility type

Receipt of immunotherapy following cancer diagnosis

Logistic regressions to examine factors associated with immunotherapy use in each of the three cancers. Separate analysis for the elderly and non-elderly samples to avoid the issue of near collinearity between age and insurance variables

Shiovitz et al. (2015) [40]

3583/76,259 (5)

Retrospective cohort

USA

Patients ≥ 18 years diagnosed with metastatic breast, colon, lung, prostate, ovarian and gastric cancers between 2001 and 2007

Chemotherapy

SEER-Medicare

Race (NHW/AI/Ans)

Age, cancer type, geographic region, year of diagnosis

Utilisation of cancer directed therapy which included chemotherapy

Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (95% CI)

Statler et al. (2019) [30]

6234/6234 (100)

Retrospective cohort

USA

Patients 18 years or older diagnosed with stage IV (defined as metastatic to a distant site, M1 per American Joint Committee on Cancer TNM Staging Criteria), hormone receptor-positive (ER + and/or PR +) and HER2 + breast cancer who received treatment between 2010 and 2015

Not specified

NCDB

Not specified

Age, race/ethnicity, comorbidities, insurance status, income, facility type, distance to treatment, grade, sites of metastases and treatment

Treatment receipt for chemotherapy and hormone (endocrine) therapy

Multivariable logistic regression analyses were conducted to identify independent predictors of treatment receipt (chemotherapy vs. hormonal therapy)

Skinner et al. (2021) [32]

608/608 (100)

Retrospective cohort

USA

Women aged ≥ 18 years, diagnosed with metastatic triple negative breast cancer (mTNBC) between 1 January 2010 and 31 January 2016

Unspecified SACT

Vector Oncology Data Warehouse

Not specified

Age, race, BMI, Insurance, region, stage, performance, comorbidities, site of metastases

Treatment receipt (PFS, OS)

Logistic regression methods were used to evaluate predictors of receipt of systemic anticancer therapy

Small et al. (2012) [41]

57,148/773,233 (7)

Retrospective cohort

USA

Patients > 18 diagnosed with stage IV cancer of kidney, uterus, NSCLC, SCLC, rectum, colon, prostate, breast and cervix between 2000 and 2008 who did not receive any first‐course therapy

Unspecified SACT

NCDB

Not specified

Age, race, ethnicity, insurance status, education, income

Receipt of no first course anticancer therapy

Log‐binomial regression to estimate prevalence ratios (PRs) with 95% confidence limits (95% CL) relating the percentages of patients receiving no first‐course therapy versus any therapy for stage IV cancer among categories of various socioeconomic and demographic variables. Statistical significance was defined as p < .05

Vas Luiz et al. (2015) [31]

4364/4364 (100)

Retrospective cohort

USA

Women > 66 with a first invasive metastatic breast cancer diagnosed between October 1998 and December 2009 enrolled in Parts A/B Medicare

Immunotherapy

SEER-Medicare

Race (White/Black)

Age, marital status, income, education, year of diagnosis, location of residence (metro/nonmetro), geographical location (SEER region), comorbidity, grade, HR status

Time to trastuzumab initiation and utilisation of trastuzumab

Wilcoxon signed-rank tests and multivariable linear regression to examine utilisation adjusting for exposure variables stratified by HR status

Vyas et al. (2021) [5]

1089/1089 (100%)

Retrospective cohort

USA

Women aged > 65 years diagnosed with HER2-negative MBC during 2010–2013

Unspecified SACT

SEER-Medicare

Not specified

Predisposing characteristics comprised age at diagnosis, race/ethnicity, whilst enabling characteristics included marital status, household income and education

Need-related factors included HR status, grade of tumour, comorbidity scores, performance status and number of sites with cancer metastasis

External care environmental factors comprised the location of residence, SEER region and census level information on the number of hospitals offering oncology services

Receipt of guideline-concordant initial treatment within the first 6 months of a cancer diagnosis

Multivariable logistic regression to identify the significant predictors of guideline-concordant treatment and a non-linear decomposition method to examine disparities by

HR status

Wan & Jubelirer (2015) [35]

4533/4533 (100)

Retrospective cohort

USA

Women > 66 diagnosed with stage IV metastatic breast cancer between 1992 and 2002

Chemotherapy

SEER-Medicare

Not specified

Age, race, ethnicity, year of diagnosis, income, marital status, HR status, comorbidities, rural/urban, geographical location (SEER region), area chemotherapy rate, travel time, oncologist provision, hospice provision

Receipt of chemotherapy within 6 months (183 days) of diagnosis

Multivariate logistic regression aggregate models with interaction terms and subgroup analyses

Wang & Du (2015) [42]

1100/25,128 (4)

Retrospective cohort

USA

Women > 65 diagnosed with hormone receptor-positive breast cancer aged between 2006 and 2009 with Part-D claims up to December 2010

Hormone therapy

SEER-Medicare

Not specified

Age, race, marital status, comorbidity, SES, geographical location (SEER region), location of residence (urban/rural), year of diagnosis, stage, grade, lymph node involvement

Receipt of hormone therapy and overall use of hormone therapy 1 year post initiation (stratified by chemotherapy use)

Multivariate logistic regression assessed variation associated with the use of hormone therapy, SERM and AIs, respectively, adjusted for age, gender, race, marriage status, SEER registry area, year of diagnosis, tumour stage, tumour size, radiation therapy status, surgery status and comorbidity

Wolfson et al. (2015) [43]

1441/75,987 (4)

Retrospective cohort

USA

Patients aged > 22 < 65 with newly diagnosed adult-onset breast, cervical colorectal, gastric, hepatobiliary, lung, oral, and pancreatic cancer between 1998 and 2008

Unspecified SACT

NCI LAC

Not specified

Age, race/ethnicity, SES, distance to nearest NCI CCC

Receipt of care which included including SACT at National Cancer Institute Comprehensive Cancer Centre (NCI CCC)

Logistic regression analysis for multivariate modelling of likelihood of receiving care at an NCICCC. Two-sided tests with p < 0.05 were considered statistically significant