Age standardized rate of cancer incidence, by selected sites of cancer and sex, three-year average, census metropolitan areas.

Background: The aggressive and heterogeneous nature of lung cancer has thwarted efforts to reduce mortality from this cancer through the use of screening. The advent of low-dose helical computed tomography (CT) altered the landscape of lung-cancer screening, with studies indicating that low-dose CT detects many tumors at early stages. The National Lung Screening Trial (NLST) was conducted to determine whether screening with low-dose CT could reduce mortality from lung cancer.

Methods: From August 2002 through April 2004, we enrolled 53,454 persons at high risk for lung cancer at 33 U.S. medical centers. Participants were randomly assigned to undergo three annual screenings with either low-dose CT (26,722 participants) or single-view posteroanterior chest radiography (26,732). Data were collected on cases of lung cancer and deaths from lung cancer that occurred through December 31, 2009. This dataset includes the low-dose CT scans from 26,254 of these subjects, as well as digitized histopathology images from 451 subjects.

Results: The rate of adherence to screening was more than 90%. The rate of positive screening tests was 24.2% with low-dose CT and 6.9% with radiography over all three rounds. A total of 96.4% of the positive screening results in the low-dose CT group and 94.5% in the radiography group were false positive results. The incidence of lung cancer was 645 cases per 100,000 person-years (1060 cancers) in the low-dose CT group, as compared with 572 cases per 100,000 person-years (941 cancers) in the radiography group (rate ratio, 1.13; 95% confidence interval [CI], 1.03 to 1.23). There were 247 deaths from lung cancer per 100,000 person-years in the low-dose CT group and 309 deaths per 100,000 person-years in the radiography group, representing a relative reduction in mortality from lung cancer with low-dose CT screening of 20.0% (95% CI, 6.8 to 26.7; P=0.004). The rate of death from any cause was reduced in the low-dose CT group, as compared with the radiography group, by 6.7% (95% CI, 1.2 to 13.6; P=0.02).

Conclusions: Screening with the use of low-dose CT reduces mortality from lung cancer. (Funded by the National Cancer Institute; National Lung Screening Trial ClinicalTrials.gov number, NCT00047385).

Data Availability: A summary of the National Lung Screening Trial and its available datasets are provided on the Cancer Data Access System (CDAS). CDAS is maintained by Information Management System (IMS), contracted by the National Cancer Institute (NCI) as keepers and statistical analyzers of the NLST trial data. The full clinical data set from NLST is available through CDAS. Users of TCIA can download without restriction a publicly distributable subset of that clinical data, along with the CT and Histopathology images collected during the trial. (These previously were restricted.)

This table contains 30810 series, with data for years 2001/2003 - 2013/2015 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (158 items: Canada; Newfoundland and Labrador; Eastern Regional Health Authority, Newfoundland and Labrador; Central Regional Health Authority, Newfoundland and Labrador; ...);  Sex (3 items: Both sexes; Males; Females);  Selected sites of cancer (ICD-O-3) (5 items: All invasive primary cancer sites (including in situ bladder); Colon, rectum and rectosigmoid junction cancer; Bronchus and lung cancer; Female breast cancer; ...);  Characteristics (13 items: Number of new cancer cases; Cancer incidence (rate per 100,000 population); Low 95% confidence interval, cancer incidence (rate per 100,000 population); High 95% confidence interval, cancer incidence (rate per 100,000 population); ...).

One-year and five-year net survival for adults (15-99) in England diagnosed with one of 29 common cancers, by age and sex.

India IN: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data was reported at 19.800 NA in 2016. This records a decrease from the previous number of 20.000 NA for 2015. India IN: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data is updated yearly, averaging 21.200 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 23.400 NA in 2000 and a record low of 19.800 NA in 2016. India IN: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

This table contains 3069 series, with data for years 1997 - 1998 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (93 items: Canada; Health and Community Services Eastern Region; Newfoundland and Labrador; Health and Community Services St. John's Region; Newfoundland and Labrador; Newfoundland and Labrador ...), Sex (3 items: Both sexes; Females; Males ...), Selected sites of cancer (ICD-9) (5 items: All malignant neoplasms (cancers);Colorectal cancer; Lung cancer; Breast cancer ...), Characteristics (3 items: Cancer incidence; Low 95% confidence interval; cancer incidence; High 95% confidence interval; cancer incidence ...).

This table contains 600 series, with data for years 1997 - 1997 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (15 items: Canada; Prince Edward Island; Newfoundland and Labrador; Nova Scotia ...), Sex (3 items: Both sexes; Females; Males ...), Selected sites of cancer (ICD-9) (4 items: Colorectal cancer; Prostate cancer; Lung cancer; Female breast cancer ...), Characteristics (5 items: Relative survival rate for cancer; High 95% confidence interval; relative survival rate for cancer; Number of cases; Low 95% confidence interval; relative survival rate for cancer ...).

Ivory Coast CI: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data was reported at 28.200 NA in 2016. This records a decrease from the previous number of 28.500 NA for 2015. Ivory Coast CI: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data is updated yearly, averaging 27.700 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 28.500 NA in 2015 and a record low of 25.200 NA in 2000. Ivory Coast CI: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank.WDI: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

This record contains raw data related to article “Incidence and predictors of hepatocellular carcinoma in patients with autoimmune hepatitis"

Abstract

Knowledge about cervical cancer screening and Human papilloma virus (HPV) influence on their awareness to the cervical cancer screening program. Most previous studies found inadequate knowledge and attitude among healthy women affect the low rate of screening. This study aimed to assess knowledge of cervical cancer screening and HPV in women who had abnormal cervical cancer screening in Bangkok. Thai women, aged ≥ 18 years old, who had abnormal cervical cancer screening and scheduled to colposcopy clinics of 10 participating hospitals were invited to participate in this cross-sectional study. The participants were asked to complete a self-answer questionnaire (Thai language). The questionnaire composed of 3 parts: (I) demographic data, (II) knowledge about cervical cancer screening and (III) knowledge about HPV. Among 499 women who answered the questionnaires, 2 had missing demographic data. The mean age of the participants was 39.28 ± 11.36 years. 70% of them had experience of cervical cancer screening, with 22.7% had previous abnormal cytologic results. Out of 14 questions, the mean score of knowledge about cervical cancer screening was 10.04 ± 2.37. Only 26.9% had good knowledge about cervical cancer screening. Nearly 96% of woman did not know that screening should be done. After excluding 110 women who had never known about HPV, 25.2% had good knowledge about HPV. From multivariable analysis, only younger age (≤ 40 years) was associated with good knowledge of cervical cancer screening and HPV. In the conclusion, only 26.9% of women in this study had good knowledge regarding cervical cancer screening. Likewise, 20.1% of women who had ever heard about HPV has good knowledge about HPV. Providing information about cervical cancer screening and HPV should improve the women’s knowledge and better adherence to the screening procedure.

This dataset presents the footprint of participation statistics in the National Bowel Cancer Screening Program (NBCSP) for people aged 50 to 74. The NBCSP began in 2006. It aims to reduce morbidity …Show full descriptionThis dataset presents the footprint of participation statistics in the National Bowel Cancer Screening Program (NBCSP) for people aged 50 to 74. The NBCSP began in 2006. It aims to reduce morbidity and mortality from bowel cancer by actively recruiting and screening the eligible target population for early detection or prevention of the disease. The data spans the years of 2015-2017 and is aggregated to Statistical Area Level 2 (SA2) geographic areas from the 2011 Australian Statistical Geography Standard (ASGS). Cancer is one of the leading causes of illness and death in Australia. Cancer screening programs aim to reduce the impact of selected cancers by facilitating early detection, intervention and treatment. Australia has three cancer screening programs: BreastScreen Australia National Cervical Screening Program (NCSP) National Bowel Cancer Screening Program (NBCSP) The National cancer screening programs participation data presents the latest cancer screening participation rates and trends for Australia's 3 national cancer screening programs. The data has been sourced from the Australian Institute of Health and Welfare (AIHW) analysis of National Bowel Cancer Screening Program register data, state and territory BreastScreen Australia register data and state and territory cervical screening register data. For further information about this dataset, visit the data source:Australian Institute of Health and Welfare - National Cancer Screening Programs Participation Data Tables. Please note: AURIN has spatially enabled the original data. Participation rates represent the percentage of people invited to screen through the NBCSP during the relevant 2-year period, who returned a completed screening test within that period or by 30 June of the following year. The number of individuals invited to screen excludes those who deferred or opted out without completing their screening test. Values assigned to n.p. in the original data have been set to null. SA2 areas were assigned to NBCSP invitees using an SA1 to SA2 correspondence. Those invitees without reliable SA1 details were mapped with a postcode to SA2 correspondences instead, which may lead to some minor inaccuracies in results. Some invitee SA1 codes and postcodes cannot be attributed to an SA2. These invitees were included in an 'Unknown' group where applicable. Some postcodes cross SA2 boundaries, leading to slight inaccuracies. Biennial screening for those aged 50-74 is not fully rolled out. During the time period reported, the specific ages invited within the 50-74 age range included 50, 54, 55, 58, 60, 64, 65, 68, 70, 72 and 74. These results calculate participation rates using the new NBCSP performance indicator specifications. This indicator now measures a 2-year invitation period and also excludes those who opted off or suspended participation. Therefore, these results cannot be compared to rates reported prior to 2014. NBCSP participation rates per area are not related to bowel cancer incidence rates. SA2 areas with a numerator less than 20 or a denominator less than 100 have been suppressed. SA2 data for the Blue Mountains - South, Christmas Island, Cocos (Keeling) Islands, Illawarra Catchment Reserve, Jervis Bay and Lord Howe Island were suppressed due to reliability concerns from low numbers in these regions. The 2015-2016 period covers 1 January 2015 to 31 December 2016, and the 2016-2017 period covers 1 January 2016 to 31 December 2017. Participation by SA2 is not available for the period 2014-2015. The number of people in different SA2s may not sum to 'Australia' total due to rounding.

Saudi Arabia SA: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data was reported at 16.400 % in 2016. This records a decrease from the previous number of 16.500 % for 2015. Saudi Arabia SA: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data is updated yearly, averaging 17.900 % from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 18.900 % in 2000 and a record low of 16.400 % in 2016. Saudi Arabia SA: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Saudi Arabia – Table SA.World Bank: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted Average;

BackgroundThe prognosis of pancreatic cancer, which is among the solid tumors associated with high mortality, is poor. There is a need to improve the overall survival rate of patients with pancreatic cancer.Materials and MethodsThe Cancer Genome Atlas (TCGA) dataset with 153 samples and the International Cancer Genome Consortium (ICGC) dataset with 235 samples were used as the discovery and validation cohorts, respectively. The least absolute shrinkage and selection operator regression was used to construct the prognostic prediction model based on the DNA methylation markers. The predictive efficiency of the model was evaluated based on the calibration curve, concordance index, receiver operating characteristic curve, area under the curve, and decision curve. The xenograft model and cellular functional experiments were used to investigate the potential role of DNAJB1 in pancreatic cancer.ResultsA prognostic prediction model based on four CpG sites (cg00609645, cg13512069, cg23811464, and cg03502002) was developed using TCGA dataset. The model effectively predicted the overall survival rate of patients with pancreatic cancer, which was verified in the ICGC dataset. Next, a nomogram model based on the independent prognostic factors was constructed to predict the overall survival rate of patients with pancreatic cancer. The nomogram model had a higher predictive value than TCGA or ICGC datasets. The low-risk group with improved prognosis exhibited less mutational frequency and high immune infiltration. The brown module with 247 genes derived from the WGCNA analysis was significantly correlated with the prognostic prediction model, tumor grade, clinical stage, and T stage. The bioinformatic analysis indicated that DNAJB1 can serve as a novel biomarker for pancreatic cancer. DNAJB1 knockdown significantly inhibited the proliferation, migration, and invasion of pancreatic cancer cells in vivo and in vitro.ConclusionThe prognostic prediction model based on four CpG sites is a new method for predicting the prognosis of patients with pancreatic cancer. The molecular characteristic analyses, including Gene Ontology, Gene Set Enrichment Analysis, mutation spectrum, and immune infiltration of the subgroups, stratified by the model provided novel insights into the initiation and development of pancreatic cancer. DNAJB1 may serve as diagnostic and prognostic biomarkers for pancreatic cancer.

This record contains raw data related to article “Low Incidence of SARS-CoV-2 in Patients with Solid Tumours on Active Treatment: An Observational Study at a Tertiary Cancer Centre in Lombardy, Italy"

Background: The incidence and prognosis of SARS-CoV-2-positive cancer patients on active oncologic treatment remain unknown. Retrospective data from China reported higher incidence and poorer outcomes with respect to the general population. We aimed to describe the real-word incidence of SARS-CoV-2 in cancer patients and the impact of oncologic therapies on the infection. Materials & Methods: In this study, we analysed all consecutive cancer patients with solid tumours undergoing active intravenous treatment (chemotherapy, immunotherapy, targeted therapy, alone or in combination) between 21 February and 30 April 2020, in a high-volume cancer centre in Lombardy, Italy. We focused on SARS-CoV-2-positive patients, reporting on the clinical characteristics of the cancer and the infection. Results: We registered 17 SARS-CoV-2-positive patients among 1267 cancer patients on active treatment, resulting in an incidence of 1.3%. The median age was 69.5 years (range 43-79). Fourteen patients (82%) required hospitalisation for COVID-19 with a median in-hospital stay of 11.5 days (range 3-58). Fourteen of the seventeen (82%) were treated for locally advanced or metastatic disease. We could not demonstrate any correlation between SARS-CoV-2 infection and tumour or treatment type. The COVID-19-related fatality rate was 29% (5/17), which was higher than that of the general population cared for in our centre (20%). Conclusions: Active oncologic treatments do not represent a risk factor for SARS-CoV-2 infection in cancer patients. However, the prognosis of infected cancer patients appears to be worse compared with that of the non-oncologic population. Given the low number of SARS-CoV-2-positive cases and the uncertainties in risk factors that may have an impact on the prognosis, we advocate for the continuum of cancer care even during the current pandemic.

The number of females who participated in a breast cancer screening program and there proportion of the relevant population, as well as the number of people diagnosed with breast cancer as a rate of those who participated, 2010-2011 (NSW, Vic, Qld, SA & WA). Source: Compiled by PHIDU based on data from BreastScreen NSW, BreastScreen Vic, BreastScreen Qld, BreastScreen WA - 2010 and 2011.The Dataset also contains the number of females who participated in a cervical cancer screening program and there proportion of the relevant population, as well as the number of the people diagnosed with low/high cervical cancer as a rate of those who participated, 2010-2011 (NSW, Vic, Qld, SA, WA & ACT). Source: Compiled by PHIDU based on data from the NSW Department of Health and NSW Central Cancer Registry, 2011 and 2012; Victorian Cervical Cytology Registry, 2011 and 2012; Queensland Health Cancer Services Screening Branch, 2011 and 2012; SA Cervix Screening Program, 2011 and 2012; Western Australia Cervical Cytology Register, 2011 and 2012; and ACT Cytology Register, 2011 and 2012.For both sets of screening if a women was screened more than twice in the two year period she is counted once only (all entries that were classified as not shown, not published or not applicable were assigned a null value; no data was provided for Maralinga Tjarutja LGA, in South Australia). The data is by LGA 2015 profile (based on the LGA 2011 geographic boundaries). For more information on statistics used please refer to the PHIDU website, available from: http://phidu.torrens.edu.au/

AbstractIn Italy, approximately 400.000 new cases of malignant tumors are recorded every year. The average of annual deaths caused by tumors, according to the Italian Cancer Registers, is about 3.5 deaths and about 2.5 per 1,000 men and women respectively, for a total of about 3 deaths every 1,000 people. Long-term (at least a decade) and spatially detailed data (up to the municipality scale) are neither easily accessible nor fully available for public consultation by the citizens, scientists, research groups, and associations. Therefore, here we present a ten-year (2009–2018) database on cancer mortality rates (in the form of Standardized Mortality Ratios, SMR) for 23 cancer macro-types in Italy on municipal, provincial, and regional scales. We aim to make easily accessible a comprehensive, ready-to-use, and openly accessible source of data on the most updated status of cancer mortality in Italy for local and national stakeholders, researchers, and policymakers and to provide researchers with ready-to-use data to perform specific studies. Methods For a given locality, year, and cause of death, the SMR is the ratio between the observed number of deaths (Om) and the number of expected deaths (Em): SMR = Om/Em (1) where Om should be an available observational data and Em is estimated as the weighted sum of age-specific population size for the given locality (ni) per age-specific death rates of the reference population (MRi): Em = sum(MRi x ni) (2) MRi could be provided by a public health organization or be estimated as the ratio between the age-specific number of deaths of reference population (Mi) to the age-specific reference population size (Ni): MRi = Mi/Ni (3) Thus, the value of Em is weighted by the age distribution of deaths and population size. SMR assumes value 1 when the number of observed and expected deaths are equal. Following eqns. (1-3), the SMR was computed for single years of the period 2009-2018 and for single cause of death as defined by the International ICD-10 classification system by using the following data: age-specific number of deaths by cause of reference population (i.e., Mi) from the Italian National Institute of Statistics (ISTAT, (http://www.istat.it/en/, last access: 26/01/2022)); age-specific census data on reference population (i.e., Ni) from ISTAT; the observed number of deaths by cause (i.e., Om) from ISTAT; the age-specific census data on population (ni); the SMR was estimated at three different level of aggregation: municipal, provincial (equivalent to the European classification NUTS 3) and regional (i.e., NUTS2). The SMR was also computed for the broad category of malignant tumors (i.e. C00-C979, hereinafter cancer macro-type C), and for the broad category of malignant tumor plus non-malignant tumors (i.e. C00-C979 plus D0-D489, hereinafter cancer macro-type CD). Lower 90% and 95% confidence intervals of 10-year average values were computed according to the Byar method.

Nigeria NG: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data was reported at 20.900 NA in 2016. This records an increase from the previous number of 20.800 NA for 2015. Nigeria NG: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data is updated yearly, averaging 21.000 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 22.600 NA in 2000 and a record low of 20.800 NA in 2015. Nigeria NG: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank.WDI: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

This dataset contains counts of deaths for California residents by ZIP Code based on information entered on death certificates. Final counts are derived from static data and include out-of-state deaths of California residents. The data tables include deaths of residents of California by ZIP Code of residence (by residence). The data are reported as totals, as well as stratified by age and gender. Deaths due to all causes (ALL) and selected underlying cause of death categories are provided. See temporal coverage for more information on which combinations are available for which years.

The cause of death categories are based solely on the underlying cause of death as coded by the International Classification of Diseases. The underlying cause of death is defined by the World Health Organization (WHO) as "the disease or injury which initiated the train of events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury." It is a single value assigned to each death based on the details as entered on the death certificate. When more than one cause is listed, the order in which they are listed can affect which cause is coded as the underlying cause. This means that similar events could be coded with different underlying causes of death depending on variations in how they were entered. Consequently, while underlying cause of death provides a convenient comparison between cause of death categories, it may not capture the full impact of each cause of death as it does not always take into account all conditions contributing to the death.

This dataset presents the footprint of participation statistics in the National Cervical Screening Program (NCSP) for women aged 20 to 69, by age group. The NCSP began in 1991. It aims to reduce cervical cancer cases, illness and deaths in Australia. The data spans the years of 2014-2016 and is aggregated to Statistical Area Level 3 (SA3) from the 2011 Australian Statistical Geography Standard (ASGS).

Cancer is one of the leading causes of illness and death in Australia. Cancer screening programs aim to reduce the impact of selected cancers by facilitating early detection, intervention and treatment. Australia has three cancer screening programs:

• BreastScreen Australia

• National Cervical Screening Program (NCSP)

• National Bowel Cancer Screening Program (NBCSP)

The National cancer screening programs participation data presents the latest cancer screening participation rates and trends for Australia's 3 national cancer screening programs. The data has been sourced from the Australian Institute of Health and Welfare (AIHW) analysis of National Bowel Cancer Screening Program register data, state and territory BreastScreen Australia register data and state and territory cervical screening register data.

For further information about this dataset, visit the data source:Australian Institute of Health and Welfare - National Cancer Screening Programs Participation Data Tables.

Please note:

• AURIN has spatially enabled the original data.

• Participation in the NCSP for this report was defined as the percentage of women in the population aged 20-69 who had at least one Pap test in a 2-year period. Participation rates were calculated using the average of the Australian Bureau of Statistics (ABS) Estimated Resident Population (ERP) for females aged 20-69 for the relevant 2-year reporting period adjusted for the estimated proportion of women who have had a hysterectomy.

• An SA3 was assigned to women using a postcode to SA3 correspondence. Because these are based only on postcode, these data will be less accurate than those published by individual states and territories.

• Postcode is used for mailing purposes and may not reflect where a woman resides.

• Some postcodes (and hence women) cannot be attributed to an SA3 and therefore these women were excluded from the analysis. This is most noticeable in the Northern Territory but affects all states and territories to some degree.

• SA3s with a numerator less than 20 or a denominator less than 100 have been suppressed.

• SA3 data for Blue Mountains - South, Christmas Island, Cocos (Keeling) Islands, Cotter - Namadgi, Fyshwick - Piallago - Hume, Illawarra Catchment Reserve, Jervis Bay, and Lord Howe Island were excluded due to reliability concerns from low numbers in these regions.

• Some duplication may occur where the same test is reported to the cervical screening register in two or more jurisdictions. This may lead to erroneous results when focusing on smaller geographical areas. This may affect border areas more than others.

• Totals may not sum due to rounding.

• Data are preliminary and subject to change.

• The 2014-2015 period covers 1 January 2014 to 31 December 2015, and the 2015-2016 period covers 1 January 2015 to 31 December 2016.

This record contains raw data related to article “The immune-metabolic-prognostic index and clinical outcomes in patients with non-small cell lung carcinoma under checkpoint inhibitors"

Abstract

Purpose: This prospective study evaluated whether peripheral blood biomarkers and metabolic parameters on F-18 fludeoxyglucose positron emission tomography/computed tomography (F-18 FDG PET/CT) could be associated with clinical outcome in non-small cell lung carcinoma (NSCLC) patients treated with immune checkpoint inhibitors (ICI).

Methods: Data from 33 patients with NSCLC and treated with ICI were collected. Complete blood cell counts before and at the first restaging were measured. All patients underwent F-18 FDG PET/CT at baseline, while 25 patients at the first restaging. Progression-free survival (PFS) and overall survival (OS) were determined and compared using the Kaplan-Meier and the log-rank test. The median follow-up was 11.3 months (range 1-17 months).

Results: Multivariate analyses demonstrated that low neutrophil-to-lymphocyte ratio (NLR < 4.9) and low total lesion glycolysis (TLG < 541.5 ml) at the first restaging were significantly associated with PFS (both p = 0.019) and OS (p = 0.001 and p = 0.048, respectively). An immune-metabolic-prognostic index (IMPI), based on post-NLR and post-TLG was developed, categorizing 3 groups: high risk, 2 factors; intermediate risk, 1 factor; low risk, 0 factors. Median PFS for low, intermediate and high risk was 7.8 months (95% CI 4.6-11.0), 5.6 months (95% CI 3.8-7.4), and 1.8 months (95% CI 1.6-2.0) (p < 0.001) respectively. Likewise, median OS was 15.2 months (95% CI 10.9-19.6), 13.2 months (95% CI 5.9-20.3), and 2.8 months (95% CI 1.4-4.2) (p < 0.001), respectively.

Conclusion: IMPI at the first restaging, combining both inflammatory and metabolic biomarkers, was correlated with PFS and OS. IMPI can be a potentially valuable tool for identifying NSCLC patients who are likely to benefit from ICI.