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Additional file 1: Table S1. Baseline characteristics of patients stratified by risk cohort. Table S2. Independent predictors of cancer in the overall cohort by Cox Regression Analysis. Table S3. Type of new primary cancer diagnosed in each cohort.

Additional file 9: Table S9. Patient-Reported Outcome Related to Other Psychosocial.

Additional file 8: Table S8. Patient-Reported Outcomes Related to Preference-Weighted Health Status.

Additional file 1: Additional Table 1. Rules for groupings into cancer types based on neoplasm and histology. Additional Table 2. Total cost by cancer type and stage, year 1 post diagnosis, diagnosed 2016-2020. Additional Table 3a. Breast cancer member characteristics by stage, diagnosed 2016-2020 comparison with USCS data as of 2019. Additional Table 3b. Cervical cancer member characteristics by stage, diagnosed 2016-2020 comparison with USCS data as of 2019. Additional Table 3c. Colorectal cancer member characteristics by stage, diagnosed 2016-2020 comparison with USCS data as of 2019. Additional Table 3d. Lung cancer member characteristics by stage, diagnosed 2016-2020 comparison with USCS data as of 2019. Additional Table 3e. Ovarian cancer member characteristics by stage, diagnosed 2016-2020 comparison with USCS data as of 2019. Additional Table 3f. Prostate cancer member characteristics by stage, diagnosed 2016-2020 comparison with USCS data as of 2019. Additional Table 4. Generalized linear regression analysis on monthly treatment costs during year 1 by stage at diagnosis. Additional Figure 1a. Breast cancer mean cost by stage at diagnosis, cumulative through year 4 post diagnosis. Additional Figure 1b. Cervical cancer mean cost by stage at diagnosis, cumulative through year 4 post diagnosis. Additional Figure 1c. Colorectal cancer mean cost by stage at diagnosis, cumulative through year 4 post diagnosis. Additional Figure 1d. Lung cancer mean cost by stage at diagnosis, cumulative through year 4 post diagnosis. Additional Figure 1e. Ovarian cancer mean cost by stage at diagnosis, cumulative through year 4 post diagnosis. Additional Figure 1f. Prostate cancer mean cost by stage at diagnosis, cumulative through year 4 post diagnosis. Additional Figure 2. Mean cancer-specific cost by cancer and stage, year 1 post diagnosis: 1-6 months and 7-12 months. Additional Figure 3a. Breast cancer mean cancer-specific cost by stage at diagnosis, year 1-4 post diagnosis. Additional Figure 3b. Cervical cancer mean cancer-specific cost by stage at diagnosis, year 1-4 post diagnosis. Additional Figure 3c. Colorectal cancer mean cancer-specific cost by stage at diagnosis, year 1-4 post diagnosis. Additional Figure 3d. Lung cancer mean cancer-specific cost by stage at diagnosis, year 1-4 post diagnosis. Additional Figure 3e. Ovarian cancer mean cancer-specific cost by stage at diagnosis, year 1-4 post diagnosis. Additional Figure 3f. Prostate cancer mean cancer-specific cost by stage at diagnosis, year 1-4 post diagnosis. Additional Figure 4a. Breast cancer mean cancer-specific cost by stage at diagnosis, cumulative through year 4 post diagnosis. Additional Figure 4b. Cervical cancer mean cancer-specific cost by stage at diagnosis, cumulative through year 4 post diagnosis. Additional Figure 4c. Colorectal cancer mean cancer-specific cost by stage at diagnosis, cumulative through year 4 post diagnosis. Additional Figure 4d. Lung cancer mean cancer-specific cost by stage at diagnosis, cumulative through year 4 post diagnosis. Additional Figure 4e. Ovarian cancer mean cancer-specific cost by stage at diagnosis, cumulative through year 4 post diagnosis. Additional Figure 4f. Prostate cancer mean cancer-specific cost by stage at diagnosis, cumulative through year 4 post diagnosis.

Additional file 3: Table S3. EMBASE Search Strategy.

Additional file 1: Table S1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Checklist.

Supplemental material, sj-docx-1-cpc-10.1177_10556656221111028 for A Systematic Review of the Cost-Effectiveness of Cleft Care in Low- and Middle-Income Countries: What is Needed? by Karen Y. Chung, George Ho, Aysegul Erman, Joanna M. Bielecki, Christopher R. Forrest and Beate Sander in The Cleft Palate-Craniofacial Journal

Estimate the annual cost of care in the 5 years following a cancer diagnosis for 17 invasive cancer types, by stage at diagnosis. We used 2012-2016 data from the Surveillance, Epidemiology, and End Results (SEER) registry-Medicare claims database to examine cost of care among Medicare beneficiaries with a confirmed cancer diagnosis based on International Classification of Diseases for Oncology, Third Edition histology codes reported in SEER. Beneficiaries contributed to the annual cost calculations (Years 1-5) using their observed time after diagnosis. Beneficiaries were continuously enrolled in fee-for-service Medicare Parts A/B and Part D during follow-up. Total, inpatient, outpatient, and pharmacy cancer-related service costs were calculated. From 2012-2016, we identified 597,778 Medicare beneficiaries with incident cancer diagnosis within 5 years (Stage I, II, III, and IV: 32.6%, 33.4%, 15.9%, and 18.0%, respectively). In Year 1, mean (standard deviation) total costs for Stage I diagnoses varied from $7,640 ($17,378) (prostate) to $94,636 ($117,636) (pancreas). Total costs increased by stage and reached $58,783 ($92,344) (prostate) to $156,982 ($175,009) (stomach) for Stage IV diagnoses in Year 1. Costs in Year 1 were significantly higher for Stage IV diagnoses than for earlier stages across all cancer types. In Years 2-5, total costs were lower than in Year 1 but continued to increase by stage. Beneficiaries diagnosed at later stages of cancer have higher costs of care (up to 7 times as much) than those diagnosed at earlier stages. Earlier cancer diagnosis may lead to more efficient treatment and decreased management cost.

Additional file 2: Table S2. MEDLINE Search Strategy.

ObjectiveTo determine if vascular risk factor (VRF), that is, smoking, arterial hypertension (HT), dyslipidaemia and diabetes, have an effect on multiple sclerosis (MS) pathology as measured by MS typical brain lesions, we have compared brain MRIs from patients with MS with and without VRF age-matched and sex-matched.MethodsBrain MRIs from five centres were scored for the presence of Dawson’s fingers (DF) and juxtacortical lesions (JCL). A regression model was built to predict the effect of each individual VRF on DF and JCL, considering age and disease duration.Results92 MS cases without VRF and 106 MS with one or more VRF (80 ever-smokers, 43 hypertensives, 25 dyslipidaemics and 10 diabetics) were included. Ever-smoking associated with a higher burden of DF (Exp(B)=1.29, 95% CI 1.10 to 1.51, pConclusionsIndividual VRF appear to affect MS-specific lesions differently. An increase in MS lesions was mainly seen in smokers; however, this VRF is most likely to be present from onset of MS, and other VRF effects may be partly mitigated by treatment. Our findings support that treating VRF and cessation of smoking may be important in the management of MS.

Supplemental material, sj-docx-1-tan-10.1177_17562864211057661 for Subcutaneous cladribine to treat multiple sclerosis: experience in 208 patients by Kimberley Allen-Philbey, Stefania De Trane, Zhifeng Mao, Cesar ��lvarez-Gonz��lez, Joela Mathews, Amy MacDougall, Andrea Stennett, Xia Zhou, Ozlem Yildiz, Ashok Adams, Lucia Bianchi, Camilla Blain, Christine Chapman, Karen Chung, Cris S Constantinescu, Catherine Dalton, Rachel A Farrell, Leonora Fisniku, Helen Ford, Bruno Gran, Jeremy Hobart, Zhaleh Khaleeli, Miriam Mattoscio, Sue Pavitt, Owen Pearson, Luca Peruzzotti-Jametti, Antonio Scalfari, Basil Sharrack, Eli Silber, Emma C Tallantyre, Stewart Webb, Benjamin P Turner, Monica Marta, Sharmilee Gnanapavan, Gunnar Juliusson, Gavin Giovannoni, David Baker and Klaus Schmierer in Therapeutic Advances in Neurological Disorders

Supplemental material, sj-docx-2-tan-10.1177_17562864211057661 for Subcutaneous cladribine to treat multiple sclerosis: experience in 208 patients by Kimberley Allen-Philbey, Stefania De Trane, Zhifeng Mao, Cesar ��lvarez-Gonz��lez, Joela Mathews, Amy MacDougall, Andrea Stennett, Xia Zhou, Ozlem Yildiz, Ashok Adams, Lucia Bianchi, Camilla Blain, Christine Chapman, Karen Chung, Cris S Constantinescu, Catherine Dalton, Rachel A Farrell, Leonora Fisniku, Helen Ford, Bruno Gran, Jeremy Hobart, Zhaleh Khaleeli, Miriam Mattoscio, Sue Pavitt, Owen Pearson, Luca Peruzzotti-Jametti, Antonio Scalfari, Basil Sharrack, Eli Silber, Emma C Tallantyre, Stewart Webb, Benjamin P Turner, Monica Marta, Sharmilee Gnanapavan, Gunnar Juliusson, Gavin Giovannoni, David Baker and Klaus Schmierer in Therapeutic Advances in Neurological Disorders