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National Program of Cancer Registries

The National Program of Cancer Registries (NPCR) is a comprehensive, population-based cancer registraton system that collects, manages, and analyzes data on the incidence of cancer in the United States.
Established by the Centers for Disease Control and Prevention (CDC), the NPCR aims to provide high-quality cancer surveillance data to inform cancer control planning and evaluation.
By leveraging the AI-driven platform of PubCompare.ai, the NPCR optimizes research protocols and enhances reproducibility, enabling researchers to locate relevant protocols from literature, pre-prints, and patents, and use intelligent comparisons to identify the best protocols and products for thier cancer research needs.
This integrated approach helps to advance cancer research and improve outcomes for patients.

Most cited protocols related to «National Program of Cancer Registries»

1
Multiplex qPCR for Diagnosis of Malaria Species
DNA was extracted from 200 μL whole blood (venous blood collected in EDTA anti-coagulant) using QIAamp 96 DNA Blood Mini Kit (QIAGEN, Valencia, CA), and eluted in a final volume of 200 μL dH2O according to the supplier's instructions. nPCR was carried out as described [22 (link)].
PCR_LDR_FMA was carried out as described elsewhere [19 (link)]. Mixes of serially diluted plasmids containing inserts of P. falciparum, P. vivax, P. malariae or P. ovale 18 S rDNA were used as positive controls in addition to P. falciparum or P. vivax positive samples obtained from field isolates. The threshold for positivity for each species was determined using the mean value obtained from negative controls for each species, plus three times the standard deviation.
The primers and probes of the qPCR assay are listed in Table 1. In the design of a duplex qPCR, the probes combined in one reaction carried different fluorescent labels at their 5' ends. All four probes carried a black hole quencher (BHQ) at their 3'ends. The analytical specificity of primers and probes were evaluated for each Plasmodium species in silico by Blast searches and experimentally by using gDNA of the three alternatives Plasmodium species or of related blood borne parasites. To minimize costs of consumables, duplex reactions were performed in a final volume of 12.5 μL. Amplification and detection of the amplified product was performed in an iQcycling BioRad system, using iQSupermix from BioRad. The P. falciparum/P. vivax (Pf/Pv) duplex reaction contained 2.5 μL DNA (corresponding to 2.5 μL whole blood), 6.25 μL SuperMix iQ (BioRad), 0.35 μL Pf primer mix (50 μM), 0.35 μL of Pv primer mix 50 μM, 0.375 μL of Pf probe (10 μM), 0.375 μL of Pv probe (10 μM) and 2.3 μL double distilled water. The P. malariae/P. ovale (Pm/Po) duplex reaction contained equivalent amounts and concentrations of the respective primers and probes. The thermal profile used was 2 minutes at 50°C, followed by 10 minutes at 95°C and 45 cycles of 15 seconds at 95°C and 1 minute at 58°C.
Rosanas-Urgell A., Mueller D., Betuela I., Barnadas C., Iga J., Zimmerman P.A., del Portillo H.A., Siba P., Mueller I, & Felger I. (2010). Comparison of diagnostic methods for the detection and quantification of the four sympatric Plasmodium species in field samples from Papua New Guinea. Malaria Journal, 9, 361.
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Publication 2010
Biological Assay BLOOD Coagulants DNA, Ribosomal Edetic Acid National Program of Cancer Registries Neoplasm Metastasis Oligonucleotide Primers Parasites Plasmids Plasmodium Veins
2
Surveillance of Tick-Borne Pathogens
A total of 4938 I. scapularis ticks collected in passive surveillance in 2012 (excluding the 68 used in validation) were tested using the developed testing protocol (Figure 
1). The screening 23S and confirmatory ospA real-time PCR were used to assess B. burgdorferi infection as described above. The screening 23S PCR is a multiplex assay that also detects the presence of A. phagocytophilum DNA using primers specific for the msp2 gene (ApMSP2f and ApMSP2r)
[14 (link)]. Confirmation of infection with A. phagocytophilum is achieved by an in-house real-time PCR assay targeting 16S rRNA. The Borrelia miyamotoi-specific IGS real-time PCR was used to detect B. miyamotoi infections that were subsequently confirmed by B. miyamotoi glpQ real-time PCR. All real-time PCR assays were conducted using the conditions described above for B. miyamotoi IGS. Tick extracts that were positive for Borrelia spp. infection in the screening 23S real-time PCR, but negative for B. burgdorferi in the ospA real-time PCR, and negative in the B. miyamotoi IGS assay, were tested by 16S-23S IGS nPCR with the aim of sequencing products to identify other infecting Borrelia species.
Associations of infections and co-infections in ticks with province of origin, level of engorgement of the tick, host of origin, and tick instar were investigated by logistic regression in STATA version 11.0 for Windows (STATACorp, College Station, TX, USA). The most parsimonious multivariable model was created by backwards and forwards elimination and substitution of variables. Logistic regression models were used to investigate whether or not there were significant associations between infections of ticks with different pathogens. The level of significance throughout was P < 0.05.
Dibernardo A., Cote T., Ogden N.H, & Lindsay L.R. (2014). The prevalence of Borrelia miyamotoi infection, and co-infections with other Borrelia spp. in Ixodes scapularis ticks collected in Canada. Parasites & Vectors, 7, 183.
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Publication 2014
Biological Assay Borrelia Borrelia Infections Coinfection Genes Hyperemia Infection Lyme Disease National Program of Cancer Registries Oligonucleotide Primers Pathogenicity Real-Time Polymerase Chain Reaction RNA, Ribosomal, 16S Ticks
3
Comprehensive Cancer Incidence and Mortality Trends
Population-based data on newly diagnosed invasive cancers were obtained from registries that participate in the NCI’s SEER Program and/or CDC’s National Program of Cancer Registries (NPCR) and submit their data to NAACCR. Site and histology were coded according to the International Classification of Diseases for Oncology (ICD-O) edition in use at the time of diagnosis and converted to the third edition coding,29 and categorized according to SEER anatomic site groups.30 Incidence rates were calculated for all cancer sites combined, childhood cancers (ages 0-14 years and 0-19 years), and for the 15 most prevalent cancers among men and women for each of the major racial and ethnic groups (white, black, Asian Pacific Islander [API], American Indian/Alaska Native [AI/AN] and Hispanic). Hispanic ethnicity includes individuals from all races identified as Hispanic. Rates for AI/ANs were based on cases and deaths occurring in counties covered by the Indian Health Service Contract Health Service Delivery Areas (CHSDA); these areas have better race/ethnicity ascertainment leading to more accurate rates for this population.10 (link), 31 (link)Incidence data were not available uniformly for every calendar year, geographic area, and racial and ethnic group in the U.S. Long-term (1992-2010) incidence trends for all racial and ethnic groups combined were based on SEER 13 registries covering approximately 13% of the U.S. population.32 , 33 Five-year (2006-2010) average annual age-adjusted incidence rates and short-term (2001-2010) incidence trends for each of the five major racial and ethnic groups and all races combined were calculated using combined data from NPCR and SEER registries (November 2012 submissions) and provided by NAACCR (December 2012 submission). U.S. population coverage was 90.1% and 85.4% for the rates and trends, respectively.
Cause of death was based on death certificate information reported to state vital statistics offices and compiled into a national file for the entire U.S. by the CDC National Center for Health Statistics’ National Vital Statistics System.34 The underlying causes of death were selected according to the International Classification of Disease (ICD) codes and selection rules in use at the time of death (ICD-8 through ICD-10) and categorized according to SEER anatomic site groups to maximize comparability between ICD and ICD-O versions.30 , 35 -37 Death rates were calculated for all cancer sites combined, childhood cancers (ages 0-14 years and 0-19 years) and for the 15 most prevalent cancers among men and women for each of the major racial and ethnic groups. We examined long-term (1975-2010) mortality trends for all racial and ethnic groups combined, five-year (2006-2010) average annual age-adjusted death rates and short-term (2001-2010) mortality trends for each of the five major racial and ethnic groups.
Edwards B.K., Noone A.M., Mariotto A.B., Simard E.P., Boscoe F.P., Henley S.J., Jemal A., Cho H., Anderson R.N., Kohler B.A., Eheman C.R, & Ward E.M. (2013). Annual Report to the Nation on the Status of Cancer, 1975-2010, Featuring Prevalence of Comorbidity and Impact on Survival among Persons with Lung, Colorectal, Breast or Prostate Cancer. Cancer, 120(9), 1290-1314.
Publication 2013
Alaskan Natives American Indians Asian Americans Body Regions Diagnosis Ethnic Groups Ethnicity Hispanics Malignant Neoplasms National Program of Cancer Registries Neoplasms Obstetric Delivery Pacific Islander Americans Woman
4
Pestivirus Typing Using Nested PCR

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Publication 2011
5' Untranslated Regions Biological Assay Bovine Viral Diarrhea Viruses Diarrhea Virus 1, Bovine Viral Diarrhea Virus 2, Bovine Viral Genes Genome National Program of Cancer Registries Oligonucleotide Primers Pestivirus PRIMM Reverse Transcriptase Polymerase Chain Reaction Strains
5
Cancer Registry Survival Analysis Across Regions
Registry data were grouped by country (Canada and United States) and within the United States (NPCR and SEER). Registries funded by both SEER and NPCR (California, Georgia, Kentucky, Louisiana, and New Jersey) were categorized as SEER because these registries are funded to meet SEER follow-up standards and their survival data have been published (24 ). The 51 participating registries were categorized as follows: Canada (Alberta, Manitoba, Nova Scotia, and Ontario); NPCR (Alabama, Alaska, Arizona, Arkansas, Colorado, Delaware, Florida, Idaho, Illinois, Indiana, Maine, Massachusetts, Michigan, Minnesota, Missouri, Montana, Nebraska, Nevada, New Hampshire, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, South Dakota, Texas, Virginia, Washington, West Virginia, Wisconsin, and Wyoming); and SEER (California, Connecticut, Georgia, Hawaii, Iowa, Kentucky, Louisiana, New Jersey, New Mexico, Utah, and metropolitan-area registries in Detroit and Seattle). To maintain confidentiality, registries were identified by randomly assigned numeric values within country and by program. Data from NPCR01 to NPCR16 contained information from NDI for deaths that occurred in 2002 through 2007 (n = 14) and/or met SEER follow-up standards (n = 3).
Survival analyses were restricted to the first primary cancer diagnosed (only cancer diagnosed or the first of multiple primary [MP] cancers diagnosed) for each cancer patient, and excluded DCO and autopsy-only cases because these cases had no calculable survival interval. To estimate the percentage of cases that were excluded from the survival analyses, we evaluated the percentage of MP cancers using SEER MP coding rules (25 ) and the percentage of DCO (including autopsy-only) cases among first primary cancers. To evaluate the breadth of case finding activities conducted by each cancer registry, we estimated the percentage of microscopically confirmed (MC) cases among first primary non-DCO cases. A patient was considered to have complete follow-up information if they were deceased (any date) or alive with last follow-up date of January 1, 2008 or later. Data from SEER registries were considered the gold standard when evaluating data from Canada and NPCR because SEER registries are funded and required to meet follow-up standards.
Weir H.K., Johnson C.J., Mariotto A.B., Turner D., Wilson R.J., Nishri D, & Ward K.C. (2014). Evaluation of North American Association of Central Cancer Registries’ (NAACCR) Data for Use in Population-Based Cancer Survival Studies. Journal of the National Cancer Institute. Monographs, 2014(49), 198-209.
Publication 2014
Autopsy Gold Malignant Neoplasms National Program of Cancer Registries Patients

Most recents protocols related to «National Program of Cancer Registries»

1
Colorectal Cancer Incidence Rates in the US
To calculate CRC incidence in the US, we used U.S. Cancer Statistics [6 ] data, which includes cancer registry data from the Centers for Disease Control and Prevention’s (CDC) National Program of Cancer Registries (NPCR) [7 ] and the National Cancer Institute’s (NCI) Surveillance, Epidemiology, and End Results (SEER) [8 ] Program. Cancer data for AI/AN persons in Alaska came from the Alaska Cancer Registry as well as the Alaska Native Tumor Registry, which is a member of the SEER program. This population-based central cancer registry records information on AI/AN persons who meet eligibility requirements for Indian Health Service benefits [9 ], who have been diagnosed with cancer in Alaska since 1969, and who resided in Alaska at the time of diagnosis.
CRC rates among AI/AN populations were calculated for six Indian Health Service regions in the US (Figure 1), and expressed per 100,000 population, using SEER*Stat software [10 ]. To examine rates by race in Alaska (Table 2), 5 years of data were aggregated because of the low number of cases in any single year for some racial groups. Rates were age-adjusted using the World Health Organization World Standard Population (2000–2025) [11 ], so that rates for AI/AN persons in the US could be compared with rates that have been estimated for countries around the world. Joinpoint [12 ] regression analysis was used to identify trends and quantify annual percent change in the CRC incidence rates among AI/AN and White persons in Alaska.

Map of United StatesIndian health service regions.

Estimates of worldwide CRC incidence were from the International Agency for Research on Cancer Global Cancer Observatory GLOBOCAN 2018 database. GLOBOCAN provides estimates of incidence rates, mortality rates, and cancer prevalence in 185 countries or territories for 36 cancer types by sex and age group [13 (link)].
Institutional review board approval and informed consent were not required for the current study because all NPCR, SEER and GLOBOCAN data are publicly available and collected for surveillance purposes, and all data were de-identified. Tribal review and approval were obtained for publication of this report from the Alaska Native Tribal Health Consortium, which is the statewide Tribal health organization serving all 229 federally recognised Tribes and all Alaska Native and American Indian individuals in Alaska.
Haverkamp D., Redwood D., Roik E., Vindigni S, & Thomas T. (2023). Elevated colorectal cancer incidence among American Indian/Alaska native persons in Alaska compared to other populations worldwide. International Journal of Circumpolar Health, 82(1), 2184749.
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Publication 2023
Age Groups Alaskan Natives American Indians Diagnosis Eligibility Determination Ethics Committees, Research Malignant Neoplasms National Program of Cancer Registries Neoplasms Racial Groups Tribes White Person
2
Molecular Detection of Anaplasma spp. in Equine Samples
Genomic DNA was extracted from the whole blood and lung tissue samples using a DNeasy Blood & Tissue Kit (Qiagen, Melbourne, Australia) following the manufacturer’s instructions. The extracted DNA was kept at −20 °C before use. PCR amplification was carried out using an AccuPower HotStart PCR Premix Kit (Bioneer, Daejeon, Republic of Korea). First, infection with Anaplasma spp. was screened via the amplification of 16S rRNA fragments using nPCR with the primer pairs EE1/EE2 and EE3/EE4 to obtain an expected amplicon of 924–926 bp in length [8 (link),9 (link)]. For species identification, the 16S rRNA genes of A. phagocytophilum and A. bovis were identified by re-amplifying the PCR-positive samples using the primer pairs EE1/EE2 and SSAP2f/SSAP2r and EE1/EE2 and AB1f/AB1r, respectively [9 (link)], to obtain the expected amplicons of 641 and 551 bp in length, respectively. The positive control for each PCR reaction comprised the A. phagocytophilum [11 (link)] and A. bovis [12 (link)] strains that were previously identified in horses from mainland Korea. For each PCR reaction, a sample with distilled water and PCR reagents but no DNA was used as the negative control.
We addressed concerns regarding the amplicon contamination of nPCR using a distinct positive control sequence to ensure the differentiation of true positive results from those caused by possible contamination. The HKG of the 18S rRNA expressed with high stability in horse tissue and cultured cells [19 (link)] was used as an internal positive control. To identify the 18S rRNA HKG, horse DNA samples were amplified using previously published primer sequences to obtain the expected 204 bp long amplicons [19 (link)]. A horse blood sample infected with C. burnetii [43 (link)] was used as the internal negative control using the primer sets EE1/EE2 and SSAP2f/SSAP2r and EE1/EE2 and AB1f/AB1r.
All primers and amplification conditions used in the present study are presented in Supplementary Table S1.
Seo M.G., Ouh I.O, & Kwak D. (2023). Detection and Genotypic Analysis of Anaplasma bovis and A. phagocytophilum in Horse Blood and Lung Tissue. International Journal of Molecular Sciences, 24(4), 3239.
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Publication 2023
Anaplasmosis BLOOD Cultured Cells Equus caballus Genome Lung National Program of Cancer Registries Oligonucleotide Primers Ribosomal RNA Genes RNA, Ribosomal, 16S RNA, Ribosomal, 18S Strains Tissues
3
Molecular Identification of Anaplasma spp. Using RFLP
A. phagocytophilum and A. bovis were identified by digesting the 16S rRNA nPCR products of 868–870 bp in length (the PCR amplicon of 924–926 bp without primer sequences) using two restriction enzymes for the RFLP assay [9 (link)]. The restriction enzymes AleI and BtgZI were used for the RFLP assay conducted using the CLC Main Workbench 6.7.2 (CLC Bio, Qiagen, Aarhus, Denmark). The solution subjected restriction digestion comprised 10 μL of PCR product, 5 μL of buffer (10×, 1 μL of AleI (10,000 U/mL; New England Biolabs, Hitchin, UK) or 2 μL of BtgZI (5000 U/mL; New England Biolabs), and distilled water to obtain a final volume of 50 μL. For BtgZI or AleI, the reactions were incubated for 1 h at 60 °C or 30 °C, respectively. The restricted fragments were separated through electrophoresis on a 3% agarose gel in TAE solution at 100 V for 60 min. The gel was then stained with ethidium bromide and subjected to UV visualization.
Seo M.G., Ouh I.O, & Kwak D. (2023). Detection and Genotypic Analysis of Anaplasma bovis and A. phagocytophilum in Horse Blood and Lung Tissue. International Journal of Molecular Sciences, 24(4), 3239.
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Publication 2023
Biological Assay Buffers CLCN7 protein, human Digestion DNA Restriction Enzymes Electrophoresis Enzyme Assays Ethidium Bromide National Program of Cancer Registries Oligonucleotide Primers Restriction Fragment Length Polymorphism RNA, Ribosomal, 16S Sepharose
4
Nested PCR for N. mikurensis Detection
Positive samples for N. mikurensis in the qPCR assay were further validated with a nested PCR assay (Figure 1). The nPCR included primers targeting the 16S rRNA gene of N. mikurensis, to amplify a 1259-bp-long amplicon (Table 1). The 25 μL reactions of the first round of amplification consisted of 12.5 μL Supreme NZYTech Taq 2× Green Master Mix (NZYTech), 0.5 μL of each of the primers Neo_16S_95_F/Neo_16S_1393_R (10 μM, Table 1), and 9 μL RNAse free water.
Szczotko M., Kubiak K., Michalski M.M., Moerbeck L., Antunes S., Domingos A, & Dmitryjuk M. (2023). Neoehrlichia mikurensis—A New Emerging Tick-Borne Pathogen in North-Eastern Poland?. Pathogens, 12(2), 307.
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Publication 2023
Biological Assay Endoribonucleases F 1393 Green S National Program of Cancer Registries Nested Polymerase Chain Reaction Oligonucleotide Primers Ribosomal RNA Genes
5
Molecular Epidemiology of Theileria parva in Vaccinated and Non-Vaccinated Cattle
Data generated from screening for T. parva DNA using p104 nPCR and genotyping using satellite markers (SSR) were entered and cleaned using Microsoft Excel. Descriptive statistics were computed at 95% confidence interval. Data from screening were analysed using Chi-square test to determine the association between outcome variable (T. parva positivity) and categorical variable (vaccination status) at statistical significance p < 0.05.
Data from genotyping were analysed using GenALEX software version 5 [24 (link)], which was used to calculate genetic diversity parameters. This included determining the mean number of alleles (Na), number of effective alleles (Ne) and expected heterozygosity (He). These parameters were used to determine parasite diversity (overall and within the parasite populations from vaccinated and non-vaccinated cattle). Principal Component Analysis (PCA) was used to determine the genetic relationships among T. parva isolates from Muguga cocktail vaccine, vaccinated and non-vaccinated cattle. Analysis of molecular variance (AMOVA) was also used to determine T. parva diversity by estimating the percentage variation within the individual population and between the two populations (vaccinated and non-vaccinated).
The detection of T. parva DNA in the vaccinated or non-vaccinated cattle blood was referred to as ‘carrier’ status since clinical ECF was not observed in the study animals. The appearance of parasite strain/genotype in the vaccinated cattle that was not similar to vaccine strains was considered as ‘breakthrough’.
Oligo S., Nanteza A., Nsubuga J., Musoba A., Kazibwe A, & Lubega G.W. (2023). East Coast Fever Carrier Status and Theileria parva Breakthrough Strains in Recently ITM Vaccinated and Non-Vaccinated Cattle in Iganga District, Eastern Uganda. Pathogens, 12(2), 295.
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Publication 2023
Alleles Animals BLOOD Cattle Genetic Diversity Genotype Heterozygote National Program of Cancer Registries Parasites Population Group Reproduction Strains T-DNA Vaccination Vaccines

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More about "National Program of Cancer Registries"

The National Program of Cancer Registries (NPCR) is a comprehensive, population-based cancer surveillance system that collects, manages, and analyzes data on the incidence of cancer in the United States.
Established by the Centers for Disease Control and Prevention (CDC), the NPCR aims to provide high-quality cancer data to inform cancer control planning and evaluation.
To enhance its research capabilities, the NPCR leverages the AI-driven platform of PubCompare.ai to optimize research protocols and improve reproducibility.
This integrated approach helps researchers locate relevant protocols from literature, preprints, and patents, and use intelligent comparisons to identify the best protocols and products for their cancer research needs.
By utilizing advanced tools like the QIAamp DNA Mini Kit, Magnesium chloride, ELISA, GelRed, Sterile ultrapure water, M2000sp system, Platinum Taq DNA polymerase, and QIAamp DNA Blood Mini Kit, the NPCR can streamline its DNA extraction, amplification, and analysis processes, ultimately advancing cancer research and improving outcomes for patients.
Additionally, the NPCR may employ the HindIII restriction endonuclease to study genetic variations related to cancer.
This comprehensive, technology-driven approach enables the NPCR to provide valuable insights and support the development of more effective cancer prevention, detection, and treatment strategies.