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What injuries should you report to WCB?
- Phoebe Simmons
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1 Employer Report of Injury Important Information How soon should you report injuries to WCB? As soon as possible. Research shows the longer the delay in reporting and managing an injury, the higher the claim costs. If you fail to report an injury within 72 hours after receiving notice or knowledge of the injury, you may be penalized up to $25,000. Complete and send the attached Employer Report to WCB or if you are a current mywcb user report online at Provide a copy of the first aid record to your worker. What injuries should you report to WCB? Work-related injuries that cause (or are likely to cause) your worker to be off work beyond the day of the injury. Injuries that require modified work beyond the day of the injury. Injuries that require medical treatment beyond first aid (e.g., physical therapy, prescription medications, chiropractic). Injuries that may result in a permanent disability ( e.g., amputations, hearing loss). SEPTEMBER 2014 What if I have additional information or concerns? Send us a letter to help us make a decision about the claim. Check the box in number 6 of the form indicating you have attached a letter. Include names, telephone numbers, and statements of any witnesses. Important: If you send a letter, please include your worker s name and Social Insurance Number, your company s name, and your signature. Employer Report of Injury form attached To report an injury Electronic: Visit mywcb Online Services for Employers at Request access online or, if you are a current user, log on to our secure connection with your user ID and password. Fax: (Edmonton) or (within Canada) If you fax the report, do not send another copy by mail. Mail to: WCB, PO Box 2415 Edmonton AB T5J 2S5 Any questions? Edmonton: Calgary: Toll Free in Alberta: Toll Free outside Alberta: a.m. - 4:30 p.m. Monday through Friday
2 Employer Report Instructions The numbers refer to question numbers on the form that may require additional explanation. If you are unclear or need assistance completing this form, call Claim Type 1 Time Lost (TL) Check this box if your worker is off work past the day of the injury. (Complete both pages of the form.) Modified Work Check this box if your worker s duties have changed because of the injury. Modified work includes a change in duties, job, hours, or amount of work. If your worker is on modified work beyond the day of the accident, the injury must be reported to WCB even if there is no time lost or loss of earnings. (Complete both pages of the form.) No Time Lost (NTL) Check this box if your worker will not miss work beyond the day of the injury. (Complete only the first page of the form.) Worker Details Please provide as much information as possible. Employer Details 2 Employer/supervisor contact Provide the contact name and number of the person in your company managing your worker s claim and return to work. Accident Details 3 Date & time of accident If the injury/condition or occupational disease developed over a period of time, indicate the date you first became aware of the injury. 4 Date accident/injury reported to employer Name the date, time, person, position and contact information. 5 Describe what happened to cause the injury Include typical actions and how often they are repeated on the job (e.g., twisting, typing, pushing, and pulling). If there is any lifting, indicate the weight. If you need more space than the area provided, please attach a letter. Example: Bob walked into our walk-in cooler to get a 50 lb. sack of potatoes. He bent down and picked up the sack, turned to his right to leave. He felt a pull in his lower back and dropped the potatoes on his right foot, also injuring his right foot. Call the claims contact centre or if you are reporting one of the following: 1. Repetitive strain injury For example, a typist developed tendonitis in the wrist as a result of job duties. Describe fully what job duties are done each day. Include the time spent at each task. 2. Occupational disease Describe hearing loss, respiratory problems, etc. due to prolonged exposure to gas, chemicals, loud noises, etc. 3. Motor vehicle accident Send us a copy of the police report, when available. 6 Location of accident Page This information may be needed to determine: whether your worker was performing duties in the course of employment, OR whether the injury occurred due to the negligence of another party. Provide a street address, if possible, indicate the location (e.g., 25 km east of Edmonton on Highway 16, an oil rig site). If it is a motor vehicle accident, include the direction of travel. Please fill in your worker s name, Social Insurance Number, and date of birth at the top of the second page in case the pages get separated. Return to Work Details 7 Please fill out all of the information that applies. Employment Type Details 2 8 Complete one of the following A or B or C of form Complete A if your worker works for you 12 months per year. Complete B if your worker works only part of the year, even though you may call the worker back to work each year. To correctly set the amount of compensation, we need to know the total number of days or months per year you would employ someone doing the same job as the injured worker, even if the work period starts and ends several times. Complete C if the injured person is an owner/operator, subcontractor, or does piece work.
3 9 Earnings Details Complete one of the following A or B A. Gross earnings Provide the worker s gross earnings for the 1 year period prior to the date of injury; or from the date the worker received a pay raise or job change in the past year; or from the date the worker was hired if less than 1 year from the date of injury. Example: Your worker was injured on June 4, Provide gross earnings for the period June 4, 2013 to June 3, A T4 slip for the previous year is not sufficient. Gross earnings include: Basic hourly, weekly, biweekly, or monthly pay Overtime pay Shift differentials Bonuses Statutory Holiday pay Gratuities The dollar value of the employersubsidized portion of employerprovided accommodation if the worker loses the accommodation because of the accident. The dollar value of an isolation allowance if the allowance is a permanent part of the job and the worker loses the allowance because of the compensable accident. The dollar value of travel, subsistence and lodging allowances if they are recorded as taxable benefits. Gross earnings not to include: Non-taxable income Severance Pay Pay in Lieu of Notice Reimbursement of Expenses Employer paid RRSP/RPP contributions Employer paid AHC premiums Employer paid group insurance premiums Dividend income B. Hourly Rate Additional taxable benefits: Vacation and statutory holiday pay Please indicate if your worker is paid holiday and stat pay as an additional percentage on their paycheque or if these days are taken as time off with pay. Shift premiums Complete if your worker receives pay in addition to the regular rate of pay (e.g., 50 paid per hour for night shift). Provide the worker s gross shift premium earnings for the one year prior to the date of injury (less if they have not worked a full year). Overtime Complete only if your worker works overtime throughout the year. Other Use this if your worker gets any other taxable earnings (e.g., permanent accommodation, company car, northern living allowance, bonus). Time missed from work without pay. These are periods your worker missed because of maternity leave, or sick leave without pay. Do not include vacation, shutdown or lack of work periods. Hours of Work Details 10 a. Number of Hours Indicate the regular hours of work, not including overtime periods. b. Does work schedule repeat? If No: Report the average number of regular hours worked per week during the year prior to the injury. Do NOT complete the work schedule. If Yes: Mark the number of regular hours worked per day in each of the boxes. Put zero for days off. Explain any codes you use in the boxes (for example, N=night, W=weekends, D=days, E=evenings). We need to know at what point in this work schedule your worker was injured to determine the compensation to pay. Circle the day in the work schedule your worker was injured. See example below. OR: If the work schedule is longer than 21 calendar days, attach a copy of the schedule. Circle the day on this work schedule that your worker was injured. Example: Your worker worked 8-hour days in the first week and 8-hour nights in the second and third weeks. Your worker was injured on the Wednesday of the second week and was off work for 2 days (Thursday and Friday). Your worker would be paid WCB benefits for 2 days. Sun Mon Tues Wed Thurs Fri Sat 8D 8D 8D D 8N 8N 8N 8N 8N 8N 8N 8N 8N 8N 8N 0 Important: Circle the day in the work schedule your worker was injured.
4 P.O. BOX 2415 EDMONTON AB T5J 2S5 Phone (in Edmonton) (toll free in Alberta) (outside Alberta) Fax or Seven Digit Claim # (if available): September 2014 EMPLOYER REPORT of Injury C040 Claim Type 1 Time Lost Modified Work Fatality Complete entire report if claim type is one of the above No Time Lost (Notice of non-disabling injury/illness) Complete fi rst page only Worker Details Last Name: First Name: Initial: Mailing Address: Apt#, Social Insurance #: City: Province: Postal Code: Personal Health #: Phone Number: Date of Birth: Gender: M F Occupation: Job description: Date hired: Does the worker have WCB personal coverage with this business? Yes No Is the worker a partner or director in this business? Yes No Is the worker an apprentice? Yes No If yes, date the worker would have obtained journeyman status: Employer Details Business Name or Government Department: WCB Account Number: Industry: Mailing Address: City: 2 Employer/Supervisor Contact Name and Title: Province: Postal Code: Contact Phone: Phone: Fax: Contact Accident Details 3 Date/time of accident: Date/time scheduled shift started: Date/time scheduled shift ended: or the injury/condition developed over time 4 Date accident/injury reported to employer: To whom was the accident/injury reported?: Phone Number: 5 Describe fully, based on the information you have, what happened to cause this injury or disease. Please describe what the worker was doing, including details about any tools, equipment, materials, etc., the worker was using. State any gas, chemicals or extreme temperatures worker may have been exposed to: If you have more information, please attach a letter. Motor vehicle accident? Yes No Cardiac condition/injury? Yes No Letter attached? Yes No Did the accident/injury occur on employer s premises? Yes No 6 Location where the accident happened (address, general location or site): Were the worker s actions at the time of injury for the purpose of your business? Yes No Were the actions part of the worker s regular duties? Yes No Injury Details What part of body was injured? (hand, eye, back, lungs, etc.) Left side Right side What type of injury is this? (sprain, strain, bruise, etc.) Employer s Signature: Date: If you have any other information that would help us make a decision, or if you have concerns, please attach a letter. THIS DOCUMENT MAY BE EXAMINED BY ANY PERSON WITH A DIRECT INTEREST IN A CLAIM THAT IS UNDER REVIEW OR APPEAL. C-040 REV SEPT 2014 Page 1 of 2
5 EMPLOYER S REPORT Page 2 of 2 Worker s Last Name: Worker s First Name: Initial: Social Insurance #: Date of Birth: 7 Return to Work Details a. Will/did you pay the worker regular pay while off work? Yes No Has the worker returned to work? Yes No b. Date and time worker fi rst missed work: c. If the worker has returned to work, indicate date: Current work status: Regular work duties, or Modifi ed work duties Regular hours of work, or Modifi ed hours of work: hrs per Pre-accident rate of pay, or Revised rate of pay: $ per If The the worker is is working modifi ed ed duties, please describe: d. If the worker is not back at work are you able to modify work duties/hours to accommodate an early return? Yes No Was offered but the worker declined e. Approximate return to work date: A Permanent position employed 12 months of the year: Full Time Part Time Irregular/Casual Does the worker have more than one position at your company? Yes No 8 Employment Type Details (Complete A or B or C. Select the worker s type of employment.) or B Non-permanent position employed only part of the year (subject to seasonal or lack of work layoffs): Seasonal worker Summer Student Temporary Position start date: Position end date: Estimated Actual How many months or days per year do you employ workers in this position? or C Alternate employment: Sub contractor Piece work Vehicle owner/operator Welder owner/operator Self-employed Volunteer Commission Other Does the worker incur expenses to perform the work (substantial materials, heavy equipment, larger tools, etc.)? Yes No Will the worker receive a T4? Yes No 9 Earnings Details Earnings information contact name (please print): 9 10 Earnings contact phone number: Earnings contact Choose A or B: A Gross earnings for the period of one year prior to the date of injury or date the worker was hired if less than one year: $ from: to Was any time missed from work without pay during the above period, excluding vacation? (eg. maternity, sick, WCB benefi ts) Yes No Dates and reasons: or B Worker s hourly rate of pay at time of accident: $ Additional taxable benefi ts: Vacation Pay Taken as time off with pay OR Paid on a regular basis % Shift Premium Gross earnings: $ from: to Overtime Gross earnings: $ from: to Other Gross earnings: $ from: to Hours of Work Details a. Number of hours (not including overtime): per Day Week Shift cycle Other: b. Does the work schedule repeat? Date shift cycle commenced: No ê Average regular hours worked per week (not including overtime): Yes è Mark hours worked for one complete work schedule (use zero for days off): Sun Mon Tues Wed Thur Fri Sat IMPORTANT Circle days of injury. See instructions or if your schedule is more than 21 days, attach a copy of the schedule. C-040 REV SEPT 2014
6 What happens when your worker is injured at work? 1 Employer Your worker immediately informs you. You complete and send a form to WCB within 72 hours. 2 Doctor Your worker sees a doctor about the injury. The doctor completes and sends a form to WCB within 48 hours of your worker s visit. 3 Worker Your worker completes a Worker Report of Injury or Occupational Disease form and sends it to WCB as soon as possible. Employer s Report Doctor s Report Worker s Report WCB registers your worker s claim and assigns it to a staff member. If more information is required to make a decision or if some is missing, WCB will contact you, your worker, or their doctor. This causes delays in payment. Claim not accepted The legislative and policy requirements were not met by the information collected. Your worker will be advised of the reason by phone and in writing. They have the option to appeal within one year. Claim accepted The legislative and policy requirements were met. Benefits and services may include Wage loss replacement Medical costs Case management services Return-to-work assistance Time lost claims No time lost claims Any questions? Appeal Edmonton: Calgary: Toll Free: WCB assigns your worker s claim to an adjudicator who makes the initial benefit decisions. If your worker needs additional rehabilitation support to return to work, the claim may be transferred from an adjudicator to a case manager. Your worker has not missed work past the day of injury, a claim process team will monitor their medical treatment. Teams also review letters and reports for evidence a claim may require adjudication. Printed on recycled paper containing 30% post-consumer waste C-040 REV SEPT 2014
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text:
Airbag Failure
576 Killed in Crashes Where Airbags Failed to Deploy
According to the National Highway Traffic Safety Administration (NHTSA), there are approximately 30,000 motor vehicle-related deaths in the U.S. each year. The number of annual auto deaths has been in decline for the past three decades due to improvements in motor vehicle safety equipment.
Airbags have been credited with saving numerous lives since they were first implemented in motor vehicles in the 1970s. Unfortunately, despite advances in technology and auto safety regulations, airbags can fail to deploy in the event of a collision.
NHTSA recorded 576 deaths in crashes where front airbags did not deploy between 2001 and 2006. According to NHTSA, of those killed, 360 victims "would have benefited from frontal airbag protection."
- Faulty wiring
- Failure to replace used airbags
- Sensor failure
- Loss of power prior to collision
- Manufacturing flaw
- Vehicle defects
- Airbags became common in the late 80s and early 90s; however, injuries and fatalities occurred in instances where a major injury was not expected due to airbag deployment.
- Airbag technology has constantly been evolving. Since the late 90s there have been several key changes to airbag designs:
- Airbag designers began "depowering" airbags starting in 1998. The new designs reduced inflation energy and the frequency of deployment in low-speed crashes.
- Federal regulations implemented in 2001 required automakers to phase in advanced airbag systems that can adjust to things such as crash severity, seat occupant, and seat belt status.
- Automakers began installing "certified-advanced airbags" in 2003. Certified-advanced airbags were required in all vehicles by 2007.
- The Fatality Analysis Reporting Systems reports that airbags failed to deploy in 18 percent of fatal frontal collisions reported between 1998 and 2006.
- The National Automotive Sampling System/Crashworthiness Data System (NASS/CDS) noted that non deployment occurred less in first generation airbags than in sled-certified airbags, 7 percent versus 11 percent respectively .
- About 2 percent of airbag non-deployment in fatal frontal collisions represented potential system failures.

subset: commoncrawl


text:
Hillary gaffe?Thursday, September 15th, 2016
Clinton controversially described half of Trump's supporters as "irredeemable." Later she put a portion of them into a basket of deplorables.
Trump earlier this year framed the same idea in a more colorful way; He stated –> "I could stand in the middle of Fifth Avenue and shoot somebody and I wouldn't lose voters."
Both statements reflect the same underlying truth: Trump enjoys a hard-core support that lies beyond persuasion, utterly immune to even the starkest factual evidence. His followers are not interested in facts or evidence. They just like his words –> "great, fantastic, and bigly.
Clinton committed a gaffe because she acknowledged a reality that literally every other person in America, including Donald Trump himself, is permitted to speak aloud. His followers are irredeemably deplorable. They aren't voting for him out of party allegiance. They voted for him because he isn't Hillary.


text:
Smart Cities That Listen
Smart cities of the future should also be able to listen to and respond to the needs of their citizens, writes Sassen.
"The word on the (everyday) street is that the smartest city of them all will be PlanIT Valley, under construction near Porto, Portugal, by Living PlanIT, founded by Steve Lewis, formerly of Microsoft. What makes PlanIT Valley different is that it is more about smart urbanism than smart systems. The concept is to build intelligent networks that combine diverse insertable and removable electronic services. In other words, the organizations charged with building and maintaining hardware and software systems can reconfigure them with reusable components as needs change. In this way, rather than allowing the technology to control the urban environment, the environment shapes the technology. With this "service-oriented architecture," one aim is to reduce the vast amount of waste in the design and construction industries by extending the lives of the design, the software, and the hardware beyond a single project.
The first phase of intelligent cities is exciting. The city becomes a living laboratory for smart urban technologies that can handle all the major systems a city requires: water, transport, security, garbage, green buildings, and clean energy."


text:
You missed it This great deal for Fizzy Peach is over. But don't despair, we've got more great products every day.
As a Nord himself, we're sure Santa would approve of dropping off these snazzy Nordic winter leggings for a special someone for only £9 (a £25.99 value) -- just don't go expecting him to show up in a pair on Christmas morning.
• Available in six stylish designs: multi snowflake, black snowflake, purple snowflake, black flower, black reindeer, or grey reindeer
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• A £3.99 delivery charge applies
Enjoy By 2 January, 2014
buy before time's up. or else kitteh gets it.
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Need a Hashimotos Test in Glenview, KY? Simply order online 24/7 and get a fast, affordable Hashimotos Test at a lab near you (Find More Locations):
What is a Hashimotos Test?
A Hashimotos Test consists of blood tests that check for Hashimoto's. People in Glenview, KY get a Hashimotos Test for general screening or at the request of a medical provider.
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Our Hashimotos Test prices include the doctor's order that you need to get tested in Glenview, KY, all lab fees and taxes, and a pdf copy of your results. For current prices, please CLICK HERE.
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text:
When you have competed in front of a global television audience and 80,000 spectators in the Beijing Bird's Nest, a new year cross-country race through the windswept wilds to the south of the Scottish Parliament could hardly be described as a pressure- cooker environment. Then again, Steph Twell was a junior athlete dipping a toe into the cauldron of the Olympic arena when she ran in the women's 1500m heats in the Chinese capital last August.
At Holyrood Park yesterday the 19-year-old from Farnborough in Hampshire bore the kind of great expectations on her shoulders that were thrust upon the young Charles Dickens when he turned up in the Scottish capital and was given his first civic reception and also the freedom of the city.
Since winning her third European junior cross-country title in Brussels a month ago, Twell has become a fully-fledged member of the senior ranks. Having emerged along similar lines to those of the young Paula Radcliffe, the highly gifted teenager has been identified as a major British prospect for 2012 and beyond. Hopes were high that she would make a significant impression in the 5.6km women's race in the Bupa Great Edinburgh International Cross Country meeting, and the army major's daughter did not disappoint.
Until the steep climb up Haggis Knowe, on the third of four laps, Twell was in contention with the leaders, battling against a clutch of world-class East Africans and winds that gusted up to 50mph. It was at that pivotal point that the Kenyan Linet Masai surged clear to a comfortable victory, in 19min 2sec.
Masai finished third in the senior race at the World Cross Country Championships on the same Holyrood course last March, fourth in the Olympic 10,000m last summer, and is the same age as Twell. The young Briton finished 14 seconds down on Masai but just three seconds shy of third place, behind Mestewat Tufa, of Ethiopia, silver medallist in the World Cross Country Championships last year, and another Kenyan, Viola Kibiwott. "I'm not totally satisfied with fourth," Twell said. "With 300 metres to go I need another injection of pace, like the other girls have at the moment. That's something I need to work on."
For all of the progress Twell has made under her astute coach of nine years, Mick Woods, she remains far from the finished article. She keeps a London 2012 badge pinned to her clothes, though if the careers of Radcliffe and the other leading British ladies of distance running down the years are anything to go by, she will not start to hit her peak until she reaches her mid-to-late 20s – in the Olympic year of 2016 and after.
Still, like Radcliffe before her, she has joined the senior ranks with a world junior title behind her, on the track at 1500m rather than at cross- country. She has also run 1500m and 5,000m quicker than Radcliffe managed at the same age. And, unlike the marathon world record holder, who missed selection for Barcelona in 1992, she has the invaluable experience of an Olympic appearance as a teenager,having narrowly missed the qualifying cut for the 1500m final in Beijing.
All of which has greatly raised those expectations. "It doesn't really faze me," Twell reflected. "I have high expectations of myself. I just embrace it rather than think of it negatively."
- More about:
- Beijing
- Marathon
- Paula Radcliffe


text:
My love
My only love thing. I hate writing of love.
All that I live,
All that I breathe,
All that I am,
All lives in the Skye.
All of my hope,
All of my dreams,
All fade into the Skye.
All of your doubts,
All of your fears,
All of your tears,
All turn you to an AcidPaintedSkye.
So I'll give,
All of my love,
All of my care,
All of my hope,
To turn you back to my Skye.


text:
Kathy Lette's latest novel is Nip 'n' Tuck, a 'shopping and tucking' tale of hitting 40 and suddenly having to deal with ageing, silicone and Husband Uncertainty Syndrome.
Buy Nip 'n' Tuck at Amazon .co.uk
"My mother always told me that beauty comes from within. Yeah, right - from within a jar marked 'Estee Lauder'. While it may seem that beauty is one of the most lovely and natural things money can buy, resist! The truth is, a woman is much more beautiful if she reads a book now and then."
1. The Picture of Dorian Gray by Oscar Wilde
There's an incurable disease afflicting females - ageing. Men, on the other hand, never pass their amuse-by dates. Sean Connery is still cutting the sex god mustard and, if time flies, then HE has frequent air miles. Yet, you never hear a man described as mutton dressed as ram, now do you? This is a book about a bloke who realises that the night is young, but he is not...
2. The Kama Sutra by Vatsysyana
Because a woman reaches her sexual prime at 40.
3. The Old Man and the Sea by Ernest Hemingway
Which suggests that recreational fishing in advanced age can be quite exciting.
4. 'Ithaca' in Collected Poems by Cavafy
Go on, pluck your highbrows! It's a good look on a girl.
5. The Catcher in the Rye by JD Salinger
To remind yourself how truly bloody awful it is being a teenager.
6. The Summer of a Dormouse by John Mortimer
Proving that every cloud has a silver-haired lining. And that the best part of us is grey - the grey matter between our ears. It's the only truly unique part of our bodies.
7. Crimes against Humanity by Geoffrey Robertson
Because despots' atrocities do tend to put a fear of wrinkles into perspective. It's good to remember that growing old is quite okay, when you consider the alternative.
8. Hedda Gabler by Henrik Ibsen
Who kills herself, rather than enjoy another day with her adoring, dim-witted husband. Life in the suburbs can be tough on some women, although on the whole it's wise to avoid the Sylvia Plath/Hedder Gabler approach to life. Nothing really disturbs kids as much as coming home to a note on the table that reads "Your mother's in the oven."
9. A Transatlantic Love Affair: Letters to Nelson Algren by Simone de Beauvoir
Though time is a great healer, it sure ain't no beauty therapist. But a toy boy, it seems, is much more rejuvenating than a face cream.
10. One Hundred Years of Solitude by Gabriel Garcia Marquez
Which shows that age is a state of mind over matter - if you don't mind, it don't matter.
Oh, and...
... almost anything by Alan Bennett, who seems to have been a woman of late middle years since he was 20.


text:
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01803 865913
+44 1803 865913
This is a revised edition of the bestselling book about the life and work...
By: James G Fox (Contributor), Richard Demarco (Contributor), Martyn Rix (Contributor), Shirley Sherwood (Contributor), Grey Gowrie (Foreword By), Rory McEwen (Illustrator)
224 pages, b/w photos, colour illustrations
This is a revised edition of the bestselling book about the life and work...
Rory McEwen: Colours of Reality showcases the botanical work and other creative talents of Rory McEwen (1932-82) ranging from the 1950s to the early 1980s. McEwen developed a distinctive style working on unadorned vellum, presenting botanical subject matter with scientific precision and artistic flair, without ever compromising one for the other. His work can be found in The British Museum, V&A, Tate, National Gallery of Modern Art Scotland and MOMA, New York, among other collections.
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text:
The YouTube channel SimpleSexyStupid has released a new video. They are delving into the expectations for how long a guy should last during sex.
It's not the most balanced video in terms of opinions, but it is fun to hear people chatting about this topic in a really laid back way.
By the end of the video it seems like the average time a guy should last is half an hour according to the women interviewed.
However, some of them do drop that time limit down quite drastically because sex can run the risk of getting boring if it goes on too long.
Here are all the interviews:
What do you guys think? Are these expectations realistic or is the data here inconclusive like many YouTube social experiments?


text:
Affiliations: From the Department of Medicine, Faculty of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada,
From the Department of Community Health Sciences, Faculty of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada,
From the Departments of Medicine, Community Health Sciences, Faculty of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada,
From the Departments of Pediatrics and Child Health, Faculty of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada
1998 by the American College of Chest Physicians
Study objectives: To identify characteristics associated with respiratory symptoms due to an episode of air pollution.
Design: Mail survey.
Setting: In October 1992, the population of the city of Winnipeg was exposed to elevated levels of particulate matter (total and <10 µm, size), carbon monoxide, nitrogen dioxide, and volatile organic compounds due to smoke from adjacent fields where farmers were burning agricultural residue (straw and stubble).
Participants: We surveyed 428 participants in the ongoing Lung Health Study (35 to 64 years old, both sexes) with mild to moderate airways obstruction (mean FEV1 percent predicted 73±12%), and a high level of airways hyperreactivity (23% of men and 37% of women).
Results: While 37% of subjects were not bothered by smoke at all, 42% reported that symptoms (cough, wheezing, chest tightness, shortness of breath) developed or became worse due to the air pollution episode and 20% reported that they had breathing trouble. Those with symptoms were more likely to be female than male and were more likely to be ex-smokers than smokers. Subjects with asthma and chronic bronchitis were also more likely affected. The degree of airways obstruction and the level of bronchial hyperresponsiveness were not associated with increased susceptibility.
Conclusions: Gender, smoking habit, and respiratory symptoms but not bronchial hyperresponsiveness or the degree of airways obstruction are factors influencing susceptibility to symptoms due to air pollution in adult smokers and former smokers.
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webcasts of the Event
More information about this event may be found here.
Tagged as: Press Releases, Webcasts
Published: March 20th, 2013
Category: News
Comments are closed.
May 24th, 2017
May 23rd, 2017
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text:
A senior PLO official declared in Amman that Mr Arafat had received an official written acceptance on Monday to his request to perform the umra. The umra, sometimes known as the little pilgrimage, can be performed throughout the year. The main haj is an annual event.
According to Arab diplomats, Mr Arafat put in a request to go on pilgrimage to Mecca when on his visit to London last month he met the Saudi ambassador, Ghazi Algosaibi. He said that before he returned to Jericho, the embryo of the Palestinian entity under the terms of the PLO-Israel accord, he wished to go on pilgrimage.
The request puts the Saudis in a delicate situation. King Fahd, who styles himself Custodian of the Two Holy Places, has a responsibility to allow Muslims to enter the country for pilgrimage, so long as they do not endager public security. However, if Mr Arafat were to enter, his visit, for ostensibly private religious purposes, would have to be accorded some official recognition.
Other signs have emerged recently of a thawing of the relations between Saudi Arabia and the PLO. On 6 January the Saudi-owned Asharq al-Awsat newspaper in London published prominently on the front page an exchange of cables between King Fahd and Mr Arafat. Mr Arafat had offered congratulations to the Saudi monarch on behalf of the PLO and himself on the inauguration of the Shura (consultative) council in Saudi Arabia.
In reply, King Fahd thanked Mr Arafat, the PLO and their 'dear people' for this sentiment and added: 'I pray to God on high to help all towards the good of our Arab and Islamic nation and the achievement of its benevolent goals, foremost among which is the realisation of the hopes and aims of the Palestinian people at this important stage of its history, in which it is building its institutions as a foundation for the building of its independent state with Jerusalem as its capital.'
For several weeks, Mr Arafat's main lieutenant in the Israeli-occupied West Bank, Faisal Husseini, has been in Saudi Arabia, seeing officials. Mr Arafat would like both political and financial support from the Saudis, who used to be the PLO's main backers. They contributed more than dollars 850m ( pounds 570m) in the 10 years from 1978 to 1988. They have now pledged dollars 50m to the Palestinian development fund, but it is payable through the World Bank, not the PLO.
- More about:
- Middle East
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text:
Development and evaluation of a virtual microscopy application for automated assessment of Ki-67 expression in breast cancer
The aim of the study was to develop a virtual microscopy enabled method for assessment of Ki-67 expression and to study the prognostic value of the automated analysis in a comprehensive series of patients with breast cancer.
Using a previously reported virtual microscopy platform and an open source image processing tool, ImageJ, a method for assessment of immunohistochemically (IHC) stained area and intensity was created. A tissue microarray (TMA) series of breast cancer specimens from 1931 patients was immunostained for Ki-67, digitized with a whole slide scanner and uploaded to an image web server. The extent of Ki-67 staining in the tumour specimens was assessed both visually and with the image analysis algorithm. The prognostic value of the computer vision assessment of Ki-67 was evaluated by comparison of distant disease-free survival in patients with low, moderate or high expression of the protein.
1648 evaluable image files from 1334 patients were analysed in less than two hours. Visual and automated Ki-67 extent of staining assessments showed a percentage agreement of 87% and weighted kappa value of 0.57. The hazard ratio for distant recurrence for patients with a computer determined moderate Ki-67 extent of staining was 1.77 (95% CI 1.31-2.37) and for high extent 2.34 (95% CI 1.76-3.10), compared to patients with a low extent. In multivariate survival analyses, automated assessment of Ki-67 extent of staining was retained as a significant prognostic factor.
Running high-throughput automated IHC algorithms on a virtual microscopy platform is feasible. Comparison of visual and automated assessments of Ki-67 expression shows moderate agreement. In multivariate survival analysis, the automated assessment of Ki-67 extent of staining is a significant and independent predictor of outcome in breast cancer.
With the emergence of virtual microscopy and whole slide scanning techniques, there is an increasing need for efficient tools to automate assessment of digitized biological samples. One possible solution is to integrate computer vision methods with a virtual microscopy platform and to run the image analysis software on the same server system as the virtual slides are stored.
A considerable number of published scientific studies have addressed computer vision for quantification of protein expression as determined by immunohistochemistry (IHC)
While tissue sample processing and IHC staining methods are increasingly automated, the evaluation of staining results is still predominantly performed by visual assessment. A human interpreter has excellent image comprehension and pattern recognition capabilities, but is prone to substantial variability in quantification tasks. Computer vision methods are capable of processing images consistently and generally perform well in repetitive processes. Virtual microscopy combined with computer vision techniques can aid the human observer by analysis of large tissue areas at a high magnification. The digital sample (i.e. the virtual slide) can be an entire section of a single cancerous tumour or an array of 100-200 tumour tissue samples assembled by the use of tissue microarray technology
We decided to develop and study a computer vision method for IHC analysis that can be run on a virtual microscopy platform and to compare the method to visual interpretation of IHC staining. A highly studied biomarker, Ki-67, with known prognostic value in many cancer forms was chosen as the target
In this study, a tool for automated quantitative assessment of Ki-67 expression is presented. The tool is implemented within a previously described web-based virtual microscopy platform
The FinProg series consist of 2842 breast cancer patients diagnosed during 1991 and 1992 within five geographical regions of Finland. The regions cover half of the population and the cases represent 53% of all breast cancers diagnosed in Finland during this period. Clinical data associated with subjects were extracted from the hospital case records, hospital registries, the Finnish Cancer Registry, and Statistics Finland. The data comprises more than 50 clinicopathological factors, including the histological type and grade of breast cancer, the number of metastatic and examined lymph nodes, primary tumour size, tumour ER and PR content evaluated by immunohistochemistry in the TMA samples, treatment details, and follow-up data. More than 50 pathologists performed histological typing and grading of cancer at the time of the diagnosis according to the World Health Organization guidelines. The median follow-up time of subjects included in the study was 9.5 years. Permission to use clinical data and formalin-fixed, paraffin-embedded tissues for research purposes was provided by the Ministry of Social Affairs and Health, Finland (permission 123/08/97). With reference to the large number of studied cases the authorities granted permission to use tissue samples without individual patient consent.
Exclusion criteria
Subjects diagnosed with ductal or lobular carcinoma in situ were excluded from the study before statistical analyses as well as those who had distant metastases at the time of the diagnosis, bilateral breast cancer, or other malignancy than breast cancer in history, except basal cell carcinoma or cervical carcinoma in situ. Since the risk of dying from these last mentioned two malignant diseases after diagnosis and proper treatment is exceedingly small, the possible confounding effect on the survival estimates was considered insignificant and not to require exclusion of the subjects. A subject was also excluded if no breast surgery was carried out. A single subject may have been excluded for one or more reasons. A consort diagram is provided in figure
Figure 1
Consort diagram
Consort diagram.
Preparation of tissue microarrays
Formalin-fixed, paraffin-embedded samples of the primary tumours (n = 1931) were collected and 1-4 tissue cores (core diameter 0.6 mm) from each patient assembled into tissue microarrays (TMAs, n = 23) as described elsewhere
Immunohistochemistry (IHC)
Immunostaining for Ki-67 was done using a mouse monoclonal antibody MM-1 (Novocastra Laboratories; 1:1,000 dilution) as previously described
Sample digitization
Twenty-three TMA slides, with 2749 tissue spots including duplicates, triplicates and quadruplicates, were digitized with an automated whole-slide scanner (Mirax Scan, Zeiss, Göttingen, Germany), using a 20× objective and a DFW-X710 camera (Sony, Tokyo, Japan). The pixel resolution was 0.26 micrometers per pixel. The virtual slides were compressed to a wavelet file format (Enhanced Compressed Wavelet, ECW, ER Mapper, Erdas Inc, Atlanta, Georgia) with a conservative compression ratio of 1:5.
Virtual microscopy platform
The computer vision algorithm was integrated with a previously described virtual microscopy platform
Computer vision algorithm
The computer vision algorithm (IhcJ) is depicted in figure
Figure 2
The IhcJ algorithm for automatic quantitative assessment of Ki-67 proliferation index
The IhcJ algorithm for automatic quantitative assessment of Ki-67 proliferation index.
The extent of staining is calculated as the total number of DAB-positive pixels divided by the union of the total number of H-positive pixels and the total number of DAB-positive pixels. The intensity of staining is calculated from DAB-positive area, as a mean pixel value of original DAB image. The mean intensity value is scaled to range from 0 to 100 percent.
Statistical analysis
For statistical analyses, only the highest extent or intensity of Ki-67 staining was considered if multiple evaluable tissue cores were available for the same patient. Continuous Ki-67 extent and intensity values generated by the computer vision algorithm were grouped. There is no consensus for cut-off values in the literature, some studies use arbitrary values, some median and some divide data in tertiles
Automated Ki-67 expression assessment
A total number of 1648 TMA spot images from the 1334 subjects were analysed in 107 minutes. There were 251 subjects with duplicate, 21 with triplicate and 7 with quadruplicate cores among the readable cases. The average analysis time for single TMA spot was 3.9 seconds. The mean and median extent of staining for Ki-67 according to the computer vision analysis was 8.8% and 4.3% (range 0-95.3%) and the mean and median intensity was 52.5% and 53.2% (range 33.9-67.0%). Sample images are displayed in figure
Figure 3
Sample images of variable area of Ki-67 staining in FinProg series
Sample images of variable area of Ki-67 staining in FinProg series. Low extent of staining (a), moderate extent of staining (b), high extent of staining (c), and corresponding result images from IhcJ macro (d, e, f).
Visual assessment of Ki-67
According to visual assessment of Ki-67 staining, 7.7% of the patients were assigned to the negative expression group, 55.7% to the moderate expression and 36.7% to the high expression group.
Association of automated assessment of Ki-67 expression with clinicopathological characteristics
When the patient series was split according to automated assessment of Ki-67 extent of staining into similar size groups as the visual Ki-67 results, 76% of the cases with high visually assessed extent had high automatically assessed extent, and none had low extent. Forty-six percent of the cases with negative visually assessed extent also had low automatically assessed extent, and only 2% had high extent (table
Table 1
Agreement between automatic and visual assessment of Ki-67 proliferation index (Kappa statistics, linear weights, Percentage agreement 87%, Kappa 0.57)
For the main analysis, we examined the relationship between automated assessment of Ki-67 expression and clinicopathological variables by splitting the series according to automated assessment of Ki-67 tertiles. Patients younger than 35 years at the time of diagnosis had a significantly higher extent of Ki-67 staining than those diagnosed at a higher age (P = 0.0008) (table
Table 2
Association of automated assessment of Ki-67 extent of staining with clinicopathological characteristics
Automated assessment of Ki-67 extent of staining
Low N (%)
Moderate N (%)
High N (%)
All tissue samples (N = 1334) *
406 (30)
446 (33)
482 (36)
Ki-67 expression (visual)
13 (3)
102 (22)
359 (76)
< 0.0001
293 (41)
314 (44)
112 (16)
82 (83)
15 (15)
2 (2)
Not available
18 (43)
15 (36)
9 (21)
Age at diagnosis (y)
< 35
2 (6)
13 (36)
21 (58)
101 (28)
120 (33)
141 (39)
160 (36)
133 (30)
149 (34)
143 (29)
180 (36)
171 (35)
Method of detection
Mammography screening
102 (41)
81 (33)
66 (27)
298 (28)
355 (34)
403 (38)
Not available
6 (21)
10 (34)
13 (45)
Primary tumour diameter (cm)
< 0.5
8 (44)
8 (44)
2 (11)
< 0.0001
82 (42)
66 (34)
49 (25)
182 (34)
180 (34)
172 (32)
104 (22)
156 (33)
212 (45)
> 5
13 (24)
14 (25)
28 (51)
Not available
17 (29)
22 (38)
19 (33)
No. of positive axillary nodes
276 (35)
253 (32)
264 (33)
80 (27)
98 (33)
119 (40)
26 (23)
45 (40)
41 (37)
≥ 10
5 (16)
11 (35)
15 (48)
Not available
19 (19)
39 (39)
43 (43
Histological grade
118 (52)
73 (32)
37 (16)
< 0.0001
122 (26)
184 (39)
171 (36)
34 (12)
67 (23)
188 (65)
Not available
132 (39)
122 (36)
86 (25)
Histological type
275 (27)
342 (34)
402 (40)
< 0.0001
87 (46)
67 (35)
36 (19)
44 (35)
37 (30)
44 (35)
ER expression
301 (35)
324 (38)
234 (27)
< 0.0001
69 (17)
102 (26)
228 (57)
Not available
36 (47)
20 (26)
20 (26)
PR expression
254 (37)
270 (39)
171 (25)
< 0.0001
122 (21)
151 (27)
295 (52)
Not available
30 (42)
25 (35)
16 (23)
HER2 amplification
34 (14)
75 (31)
134 (55)
< 0.0001
331 (33)
333 (34)
327 (33)
Not available
41 (41)
38 (38)
21 (21)
HER2 expression
26 (13)
60 (29)
121 (58)
< 0.0001
333 (33)
340 (34)
324 (33)
Not available
47 (36)
46 (35)
37 (28)
p53 expression
16 (7)
50 (22)
158 (71)
< 0.0001
98 (27)
135 (37)
129 (36)
222 (39)
196 (34)
155 (27)
Not available
70 (40)
65 (37)
40 (23)
Molecular subtype
11 (12)
15 (16)
69 (73)
< 0.0001
14 (12)
33 (28)
70 (60)
Luminal A
291 (38)
288 (37)
191 (25)
Luminal B
19 (16)
37 (32)
60 (52)
Five-marker negative
8 (19)
6 (14)
28 (67)
9 (16)
18 (32)
29 (52)
Not available
54 (39)
49 (36)
35 (25)
* due to ties the number of samples in each tertile is not equal
Uni- and multivariate analyses of distant disease-free survival
Increasing extent of Ki-67 staining as determined by image analysis is significantly associated with a decrease in distant disease-free survival (DDFS; figure
Figure 4
Distant disease-free survival (Kaplan-Meier curves, whole dataset)
Distant disease-free survival (Kaplan-Meier curves, whole dataset). by the grouped Ki-67 extent of stainings (a), and by the grouped Ki-67 staining intensities (b).
Table 3
Cox uni- and multivariate distant disease-free survival analyses
Covariate (univariate analyses)
Ki-67 (Automated assessment of extent of staining)
< 0.0001
< 0.0001
Ki-67 (Visually assessed proliferation index)
< 0.0001
Covariate (multivariate analyses)
Ki-67 (Automated assessment of extent of staining)
Tumour size*
< 0.0001
No. of positive axillary lymph nodes†
< 0.0001
Histological grade (grade 3 or 2 vs. 1)
Detection at mammography screening
Age at diagnosis
< 50
Ki-67 (Visually assessed proliferation index)
Tumour size*
< 0.0001
No. of positive axillary lymph nodes†
< 0.0001
Histological grade (grade 3 or 2 vs. 1)
< 0.0001
Detection at mammography screening
Age at diagnosis
< 50
*Hazard provided per one centimetre of the longest diameter of the tumour
†Hazard provided per one metastatic node
Table 4
5- and 10-year survival
Automated assessment of Ki-67
extent of staining
5-year survival
10-year survival
89 % (85%-92%)
81% (77%-85%)
77% (72%-80%)
71% (66%-75%)
69% (65%-73%)
64% (60%-69%)
In subgroup analysis according to histological grade, patients with grade 1 tumours and moderate automated assessment of Ki-67 extent had a hazard ratio of 1.05 (95% CI 0.35-3.22) and patients with high automated assessment of Ki-67 extent a hazard ratio of 4.63 (95% CI 1.83-11.75), as compared to patients with low automated assessment of Ki-67 extent. In patients with grade 2 tumours, the corresponding figures were 1.51 (95% CI 0.95-2.42) and 1.99 (95% CI 1.26-3.15). In the grade 3 subgroup, the results were 1.37 (95% CI 0.69-2.73) and 0.97 (95% CI 0.51-1.84). In the subgroup of patients with ductal breast cancer, the figures were 1.83 (95% CI 1.30-2.58) and 2.30 (95% CI 1.66-3.18), and in the lobular carcinoma subgroup, the corresponding hazard ratios were 1.40 (95% CI 0.67-2.93) and 2.29 (95% CI 1.06-4.95).
When extent of Ki-67 staining was determined visually, patients with a moderate visually assessed Ki-67 expression had a hazard ratio of 1.41 (95% CI 0.83-2.39) for distant recurrence, and those with a high visually assessed Ki-67 expression had a hazard ratio of 2.58 (95% CI 1.52-4.37), as compared to patients with a negative visually assessed Ki-67 expression.
For computer determined Ki-67 intensities, no statistically significant difference was observed between low and moderate intensity groups (figure
In a multivariate survival analysis, adjusted for tumour size, the number of positive lymph nodes, histological grade, method of detection and age at diagnosis, patients with a moderate automated assessment of Ki-67 extent of staining had a hazard ratio of 1.62 (95% CI 1.10-2.39) and those with high Ki-67 extent a hazard ratio of 1.73 (95% CI 1.19-2.51), compared to patients with low automated assessment of Ki-67 extent of staining (table
In the current report we describe the integration of an open source image analysis tool with a virtual microscopy platform. Computer determined extent of immunohistochemical staining of the extensively studied biomarker Ki-67 shows prognostic value comparable to visually assessed Ki-67 in a comprehensive series of patients with breast cancer.
The automated assessment of Ki-67 extent of staining was significantly associated with all the examined clinicopathological characteristics, including tumour size, number of positive lymph nodes, histological type and grade, oestrogen and progesterone receptor status, age at diagnosis, method of tumour detection, as well as molecular subtypes. These findings are in good agreement with previously reported results on the association between Ki-67 expression and clinicopathological factors
The analysis of distant disease-free survival shows that the automated assessment of Ki-67 extent of staining is a significant predictor of outcome in breast cancer. When compared to low extent of Ki-67 staining, moderate and high extent of staining is associated with hazard ratios of 1.77 and 2.34 for distant recurrence during the follow-up period. These results are in line with previous meta-analyses, where the pooled hazard ratios for disease-free survival (DFS) associated visually determined Ki-67 overexpression have been 1.93-2.18
When other variables are taken into account in the multivariate survival analysis, the automated assessment of Ki-67 extent of staining remains as a significant prognostic factor with hazard ratios of 1.62 and 1.73 for moderate and high extent of staining groups, respectively. Thus, the automated assessment of Ki-67 extent of staining is an independent predictor of patient outcome after adjustment for established clinicopathological factors. Also this is in agreement with results of meta-analyses, where a pooled DFS hazard ratio for Ki-67 overexpression in multivariate analysis was reported to be 1.76-1.84
The strengths of this study include that we analysed a large unselected breast cancer series with long follow-up period. The software and algorithms that were utilized are open source and integrated into a virtual microscopy platform. They could be made freely available as a software service on a public web site. Examples of this approach have recently been published and represent a promising methodology for standardization of quantitative immunostaining assessment and fluorescence in situ hybridization (FISH) signal counting
A weakness of the algorithm proposed in our study is the need for manual adjustment of threshold levels before starting the batch analysis. A constant threshold level for the image analysis algorithm seems acceptable if similar tissue processing and staining protocols are applied throughout the whole specimen series, as in the current study. Another weakness of the current computer vision approach is that also stromal components of tissue samples were included in the automated assessment. This affects the distribution of the extent of staining as compared to studies that have excluded tumour stroma and calculated the proportion of stained cells in the tumour parenchyma only. An approach that does not exclude stroma might be acceptable for analysis of tissue microarrays that have been constructed to mainly contain tumour tissue. However, also in the TMAs the ratio of stroma to tumour epithelium can vary according to tumour grade and histological type, which can affect the extent of staining. Therefore we performed subgroup analysis according to histological grade and type, as well as adjusted for these possible confounders in a multivariate survival model. The automated assessment of Ki-67 extent of staining was a significant prognostic factor in all subgroups, except for in the group of patients with poorly differentiated tumours. This is in line with previous results showing a lack of prognostic value of Ki-67 in grade 3 tumours
We conclude that the extent of Ki-67 staining determined by automated image analysis algorithm is an independent predictor of survival in breast cancer based on multivariate survival analysis. In univariate analysis, the automated assessment of Ki-67 extent of staining yields comparable results to the visual Ki-67 assessment. The current approach could be utilized in screening of prognostic biomarkers in large series of tissue microarrays, by integration with whole slide microscopy imaging and virtual microscopy.
Declaration of competing interests
The authors declare that they have no competing interests.
Authors' contributions
JK participated in the design of the study, assembled the image analysis system, performed data analysis and interpretation, statistical analysis and manuscript preparation. ML wrote the code for the virtual microscopy platform, participated in data acquisition and analysis, and manuscript revision. HJ and JL devised the nationwide FinProg breast cancer study. HJ supervised the FinProg study, and participated in manuscript revision. KH, TT-H, VK and LS participated in data acquisition and manuscript revision. TL assembled the tissue microarrays and participated in data acquisition and manuscript revision. HS performed staining of the samples and visual interpretation of the staining results, and participated in manuscript revision. JI supervised the laboratory work, contributed to the design of the image analysis system, and participated in data acquisition and manuscript revision. JL designed the study, performed data analysis and interpretation, statistical analysis and manuscript preparation. All authors read and approved the final manuscript.
Role of the Funding Source
The study sponsors had no involvements in the study design, in the collection, analysis and interpretation of data; in the writing of the manuscript; and in the decision to submit the manuscript for publication.
This study was supported by the Finnish Cancer Society, Sigrid Juselius Foundation, Finska Läkaresällskapet, Medicinska Understödsföreningen Liv och Hälsa, and a Special Governmental Research Grant (EVO/TYH 2010106).
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Evaluation of residual cellularity and proliferation on preoperatively treated breast cancer: a comparison between image analysis and light microscopy analysis
Combined Ki-67 and Feulgen stain for morphometric determination of the Ki-67 labelling index
Estrogen and progesterone receptor status determined by the Ventana ES 320 automated immunohistochemical stainer and the CAS 200 image analyzer in 236 early-stage breast carcinomas: prognostic significance
Assessment of proliferative activity in breast cancer: MIB-1 immunohistochemistry versus mitotic figure count
The important prognostic value of Ki-67 expression as determined by image analysis in breast cancer
Assessment of the new proliferation marker MIB1 in breast carcinoma using image analysis: associations with other prognostic factors and survival
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Microvessel area using automated image analysis is reproducible and is associated with prognosis in breast cancer
Inter-observer reproducibility of HER2 immunohistochemical assessment and concordance with fluorescent in situ hybridization (FISH): pathologist assessment compared to quantitative image analysis
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ImmunoRatio: a publicly available web application for quantitative image analysis of estrogen receptor (ER), progesterone receptor (PR), and Ki-67
Tissue microarrays for high-throughput molecular profiling of tumor specimens
Ki-67 as prognostic marker in early breast cancer: a meta-analysis of published studies involving 12,155 patients
Prognostic significance of tumor cell proliferation rate as determined by the MIB-1 antibody in breast carcinoma: its relationship with vimentin and p53 protein
Correlation between p53, c-erbB-2, and topoisomerase II alpha expression, DNA ploidy, hormonal receptor status and proliferation in 356 node-negative breast carcinomas: Prognostic implications
Proliferation markers and survival in early breast cancer: a systematic review and meta-analysis of 85 studies in 32,825 patients
A digital atlas of breast histopathology: an application of web based virtual microscopy
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The prognostic value of Ki67 is dependent on estrogen receptor status and histological grade in premenopausal patients with node-negative breast cancer
Membranous and cytoplasmic staining of Ki67 is associated with HER2 and ER status in invasive breast carcinoma
Pre-publication history
The pre-publication history for this paper can be accessed here:


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Everybody Hates RaymondMature
An imaginary behind the scenes view of one of my favorite television shows.
In 1996 , CBS debuted Everybody Loves Raymond , a sitcom about a hapless Joe named Ray Barone. Ray is the kind of guy who shirks most of his responsibilities , such as helping out around the house , and watching the kids. Instead , he would rather devote his time to what makes him happy , being a couch potato , playing golf , and hanging out with his buddies at Nemo's.
Not only is he irresponsible , but he's insensitive to his wife's feelings , as he demonstrates in every episode , which is one of the reasons they argue. Another is his lack of his responsibility.
The series is based loosely on the comedy of Ray Romano. It was successful in the ratings , and ran for nine seasons before it was cancelled in 2005. It also starred Brad Garrett , as Ray's older brother , Robert , who is jealous , and whines constantly about Ray being the favored one. The elder Barones are portrayed by Doris Roberts , as Marie , and Peter Boyle , as Frank. Marie constantly pampers Ray - which is the source of Robert's resentment - and is always arguing with Frank , who insults her at every opportunity , much of it having to with their marriage. Ray's wife , Deborah , is portrayed by Patricia Heaton. In every episode , Ray manages to put his foot in his mouth by saying , or doing something insensitive , and they wind up arguing.
After the series ended , one of the producers , Lisa Jackson , published a book about the cast and their experiences working together. The book , Everybody Hates Raymond , was a tell all that left virtually nothing to the imagination. According to Jackson , the entire cast , with the exception of the children , were exactly like their characters on the show.
From the book : "They were the mirror images of their characters , which is why they were chosen. Ray was a lazy , irresponsible jerk wad ; Patricia was an angry , bitchy woman ; Brad was a whiny crybaby ; Peter a gassy , insulting bastard , and Doris believed that she was God's gift to mothers.
"This pleased Philip immensely. He believed that as long as they were clones of their characters , they would have no trouble playing their roles. And getting into character and staying there from beginning , to end of series , should not be a problem. The only problem that Philip had with these people , which was not really a problem , depending on your perspective , was that they hated each other. They genuinely hated each other. They were always fighting and bickering among themselves , just like their characters on the show. They fought like cats and dogs , about anything and everything. Every day that I came to the set , I heard voices arguing somewhere , or someone screaming at someone else. They argued and fought during rehearsal , and they argued and fought during taping.
"One of the things they fought about was Peter's disgusting flatulence. He was constantly letting loose. The studio stank like an out house , or a sewer. No one wanted to rehearse or tape with Peter tooting all over the place. It was disgusting. We all had to wear gas masks , which made it difficult for the cast to read their lines , because Peter wouldn't stop tooting. Apparently , he didn't mind his own stench , even though it was bad enough to kill the devil himself , and each time he let loose , we wanted to kill him.
"Another thing they fought about was Doris's drinking. The woman was a lush and couldn't lay off the booze if her life depended on it. She drank like a fish. She loved alcohol in general , but preferred beer to anything else. She left empty cans and bottles all over the studio , the set , and in everyone's dressing rooms - including her own. When she was drunk - which was most of the time - she would barge into everyone's dressing rooms , whether they were there or not , and challenge them to a drinking contest. If a room was unoccupied , she would blabber at the walls , thinking she was talking to an actual person , completely oblivious to the fact that no one answered her back. Of course , no one ever took her up on her challenge. They would scream at her to get out , calling her a crazy old bitch , and slam the door in her face.
They would lock the doors to keep her out , but that didn't do any good. She would pick the locks , even while blind , stinking drunk , leave her empties , and leave the doors open. This went on for some time. Everyone complained numerous times to Philip. He said he would take care of it , but of course he never did. He didn't own the studio , so there was really nothing he could do. And there was no proof that it was Doris that was littering the studio. No one had actually seen her doing it. It was their word against hers.
"Doris had other problems other than drinking. When she wasn't challenging someone to a drinking contest , she could usually be found arguing with Patricia. On the show , Pat's character , Debra , resented the elder Barones' always barging in uninvited and unannounced , and when Doris was drunk , she sometimes forgot who she was. When she was drinking , she actually believed she was Marie Barone. So , much of the time , when she was plastered , she would deliberately pick fights with Patricia. She would pound on her dressing room door , or confront her in front of everyone else , accusing her of being an angry bitch who liked to bully people.
" 'I don't know what my Ramey sees in you!' she screamed one day. 'Sometimes I think you stay married to him jus' so you can blame him for all your prolems!'
"Patricia knew she was drunk as usual. 'Get lost you crazy old bat!' she said , shoving her.
Doris fell flat on her back and didn't get up. In fact , she didn't move for almost thirty seconds , and Patricia was starting to get worried.
" 'Oh my God! I didn't kill the old witch , did I?!'
"She ran from the room to get help , not realizing that Doris had only fallen asleep. When she came back , she was dragging Brad Garrett with her. By now , Doris's mouth was hanging wide open , and she was snoring loudly. A string of saliva had dribbled down her chin , and a fly was slacking it's thirst at it , as if it were a miniature fountain.
" 'She doesn't look dead to me!' Brad said irritably. He shook her awake and helped her up.
"Doris looked around groggily. 'whuz goin' on?'
" 'Patricia thought she killed you.'
"Doris's blood shot eyes widened. 'Now I remember! You pushed me , you tramp!'
"She grabbed Patricia , and the two of them rolled around the room , screaming and pulling each others hair out. Brad attempted to get them to stop , screaming at them as loud as he could , but they couldn't hear him above their own screaming.
"A few minutes later , Ray came running into the room. 'What's going on here?!' he shouted.
"Patricia and Doris finally stopped fighting and looked up at him. Their hands were full of chunks of each others hair , and there were several bald spots on their heads. They looked ridiculous.
"'You!' Doris said.
" 'You!' Patricia said. 'This is all your fault!'
" 'My fault!?' he said. 'What did I do?'
" 'Give me a minute and I'll think of something. Come here , so I can Kill you!'
Brad was insanely jealous , because of all the attention Ray got , both on and off the show , and in every episode he always said the same thing. And it didn't matter that they wanted to kill him. He was still jealous.
" 'Everybody loves Raymond ,' he said.